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1. Coarse large-eddy simulations in a transitional wake flow with flow models under location uncertainty

Author: Pranav Chandramouli, Sylvain Laizet, Dominique Heitz, Etienne Mémin, Fluid Flow Analysis, Description and Control from Image Sequences ( FLUMINANCE ), Institut de Recherche Mathématique de Rennes ( IRMAR ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -AGROCAMPUS OUEST-École normale supérieure - Rennes ( ENS Rennes ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National des Sciences Appliquées ( INSA ) -Université de Rennes 2 ( UR2 ), Université de Rennes ( UNIV-RENNES ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Centre National de la Recherche Scientifique ( CNRS ) -Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture ( IRSTEA ) -Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique ( Inria ), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement ( UR OPAALE ), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture ( IRSTEA ), Imperial College London, Fluid Flow Analysis, Description and Control from Image Sequences (FLUMINANCE), Institut de Recherche Mathématique de Rennes (IRMAR), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-INSTITUT AGRO Agrocampus Ouest, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Inria Rennes – Bretagne Atlantique, Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS), AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-AGROCAMPUS OUEST, Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Inria Rennes – Bretagne Atlantique, Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA), and ANR-11-LABX-0020,LEBESGUE,Centre de Mathématiques Henri Lebesgue : fondements, interactions, applications et Formation(2011)
Subjects: [PHYS.PHYS.PHYS-FLU-DYN]Physics [physics]/Physics [physics]/Fluid Dynamics [physics.flu-dyn], General Computer Science, Direct numerical simulation, Computational fluid dynamics, Wake, 0915 Interdisciplinary Engineering, 01 natural sciences, 010305 fluids & plasmas, WAKES, Physics::Fluid Dynamics, symbols.namesake, 0102 Applied Mathematics, COARSER RESOLUTION, 0103 physical sciences, SUBGRID SCALE MODELS, LARGE EDDY SIMULATION, Statistical physics, MODERATE REYNOLDS NUMBERS, 0101 mathematics, MODEL PERFORMANCE, STATISTICAL COMPARISONS, Mathematics, Curl (mathematics), LARGE-EDDY SIMULATION, business.industry, Applied Mathematics, CYLINDER WAKE FLOW, STREAMWISE VORTICES, General Engineering, Reynolds number, LOCATION UNCERTAINTY, Vortex, 010101 applied mathematics, COMPUTATIONAL FLUID DYNAMICS, symbols, CYLINDER WAKE, CYLINDERS (SHAPES), [ PHYS.PHYS.PHYS-FLU-DYN ] Physics [physics]/Physics [physics]/Fluid Dynamics [physics.flu-dyn], business, REYNOLDS NUMBER, Numerical stability, Large eddy simulation, 0913 Mechanical Engineering
Abstract: [Departement_IRSTEA]Ecotechnologies [TR1_IRSTEA]SPEE [ADD1_IRSTEA]Sûreté alimentaire; International audience; The focus of this paper is to perform coarse-grid large eddy simulation (LES) using recently developed sub-grid scale (SGS) models of cylinder wake flow at Reynolds number (Re) of 3900. As we approach coarser resolutions, a drop in accuracy is noted for all LES models but more importantly, the numerical stability of classical models is called into question. The objective is to identify a statistically accurate, stable sub-grid scale (SGS) model for this transitional flow at a coarse resolution. The proposed new models under location uncertainty (MULU) are applied in a deterministic coarse LES context and the statistical results are compared with variants of the Smagorinsky model and various reference data-sets (both experimental and Direct Numerical Simulation (DNS)). MULU are shown to better estimate statistics for coarse resolution (at 0.46% the cost of a DNS) while being numerically stable. The performance of the MULU is studied through statistical comparisons , energy spectra, and sub-grid scale (SGS) contributions. The physics behind the MULU are characterised and explored using divergence and curl functions. The additional terms present (velocity bias) in the MULU are shown to improve model performance. The spanwise periodicity observed at low Reynolds is achieved at this moderate Reynolds number through the curl function, in coherence with the birth of streamwise vortices.
Published: 2018
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2. 4D Turbulent Wake Reconstruction using Large Eddy Simulation based Variational Data Assimilation

Author: Pranav Chandramouli, Dominique Heitz, Etienne Mémin, Fluid Flow Analysis, Description and Control from Image Sequences ( FLUMINANCE ), Institut de Recherche Mathématique de Rennes ( IRMAR ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -AGROCAMPUS OUEST-École normale supérieure - Rennes ( ENS Rennes ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National des Sciences Appliquées ( INSA ) -Université de Rennes 2 ( UR2 ), Université de Rennes ( UNIV-RENNES ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Centre National de la Recherche Scientifique ( CNRS ) -Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture ( IRSTEA ) -Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique ( Inria ), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement ( UR OPAALE ), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture ( IRSTEA ), Jan F. G. Schneiders and Andreas Schröder (Eds), Fluid Flow Analysis, Description and Control from Image Sequences (FLUMINANCE), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut de Recherche Mathématique de Rennes (IRMAR), Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Institut de Recherche Mathématique de Rennes (IRMAR), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-INSTITUT AGRO Agrocampus Ouest, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), ANR-11-LABX-0020,LEBESGUE,Centre de Mathématiques Henri Lebesgue : fondements, interactions, applications et Formation(2011), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Inria Rennes – Bretagne Atlantique, AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-AGROCAMPUS OUEST, Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Inria Rennes – Bretagne Atlantique, Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)
Subjects: [ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC], [ INFO.INFO-MO ] Computer Science [cs]/Modeling and Simulation, [ MATH.MATH-MP ] Mathematics [math]/Mathematical Physics [math-ph], [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Wake flow, [SPI.MECA.MEFL]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph], Turbulence, DATA ASSMILATION, Data assimiliation, [MATH.MATH-MP]Mathematics [math]/Mathematical Physics [math-ph], LES, [SDE]Environmental Sciences, [ SPI.MECA.MEFL ] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph], [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], CFD
Abstract: International audience; Data Assimilation (DA) has been used as an effective tool for guiding simulations with observation data-sets for the better part of last few decades. However, DA has been mainly limited to applications within weather/meteorological studies with only recent excursions into conventional fluid dynamics. The limitations of computational fluid dynamics (CFD) due to complex or unknown boundary conditions and/or initial conditions can be alleviated using experimental observations through DA. Recent applications of such methodologies include [1] and [2] among many others. However, due to large computational power requirement, DA remains restricted to either 2D flows or to low Reynolds number (Re) 3D flows. A reduction in computational requirement is necessary to facilitate simulation of 3D higher Re flows. This can be achieved by using Large Eddy Simulation (LES) models within DA. This study proposes to perform Variational DA (VDA) with the adjoint of the Navier-Stokes equation using a LES model within DA to reduce computational cost. An initial study of several sub-grid scale (SGS) models (see figure 1) have shown the newly developed Models under Location Uncertainty (MULC – StSp/StSm) to perform well for various turbulent flows [3]. In addition, these models can be shown to produce accurate results at just 0.46% the cost of performing a DNS making them ideal for performing DA with LES at reduced cost. In this work, the application of the MULC to VDA are analysed for the case of wake flow over a circular cylinder for a transitional Re of 3900. The 4DVar code (Incompact3d) of [2], who performed DNS based VDA for wake flow around a circular cylinder at Re 300, has been modified to include the SGS model. The adjoint is constructed using an auto-differentiation tool – tapenade [4]. Preliminary results are shown with synthetic data-sets and an optimal reconstruction is obtained using VDA with the MULC. Future studies include performing VDA using PIV data-sets as well as using DA to characterise the SGS model coefficient.
Published: 2017

3. Méthodes variationnelles d'ensembles en assimilation de données

Author: Yin Yang, Shengze Cai, Etienne Mémin, Dominique Heitz, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Fluid Flow Analysis, Description and Control from Image Sequences (FLUMINANCE), Institut de Recherche Mathématique de Rennes (IRMAR), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-INSTITUT AGRO Agrocampus Ouest, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Inria Rennes – Bretagne Atlantique, Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement ( UR OPAALE ), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture ( IRSTEA ), Fluid Flow Analysis, Description and Control from Image Sequences ( FLUMINANCE ), Institut de Recherche Mathématique de Rennes ( IRMAR ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -AGROCAMPUS OUEST-École normale supérieure - Rennes ( ENS Rennes ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National des Sciences Appliquées ( INSA ) -Université de Rennes 2 ( UR2 ), Université de Rennes ( UNIV-RENNES ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Centre National de la Recherche Scientifique ( CNRS ) -Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture ( IRSTEA ) -Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique ( Inria ), ANR-11-LABX-0020,LEBESGUE,Centre de Mathématiques Henri Lebesgue : fondements, interactions, applications et Formation(2011), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut de Recherche Mathématique de Rennes (IRMAR), AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-AGROCAMPUS OUEST, Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA), and Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Inria Rennes – Bretagne Atlantique
Subjects: [ INFO.INFO-MO ] Computer Science [cs]/Modeling and Simulation, DATA ASSIMILATION, [SDE]Environmental Sciences, [ SPI.MECA.MEFL ] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph], [ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing, METHODE ENVAR, ENVAR, FLUID MECHANICS, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [SPI.MECA.MEFL]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph]
Abstract: [Departement_IRSTEA]Ecotechnologies [TR1_IRSTEA]SPEE; International audience; Ensemble-Variational (EnVar) methods have been drawn attention to the Data Assimilation community over the last decade. They open an alternative way between variational adjoint-based method and filtering probabilistic-based method. One major advantage of EnVar, compared to variational methods, is that the adjoint model can be avoided. Thus the EnVar is more portable and much easier to be deployed to the operational scenario in case of change of model because it is largely model-independent. Also, EnVar is proved to be an appropriate method able to tacking nonlinear non-Gaussian problems with considerable precision under reasonable computational cost. So we believe that this method constitutes a promising approach for flow measurement problems. We are investigating the EnVar methods, for recovering the unknown state/parameter fields of non-trivial dynamic models by assimilating different types of image data of high resolution [1, 3]. We will show the performance and effectiveness of the EnVar method on Kinect captured depth-range data combined with shallow water model as well as synthetic SST image combined with the SQG model. More specifically we establish a stochastic dynamical formulation allowing explicitly taking into account of the subgrid effects resulted from scale discrepancy and we employ an augmented EnVar to identify those uncertainty parameters [2]. Fig. 1 Velocity vectors at initial time: (a) the ground-truth vorticity map; (b) the motion vectors of the ground-truth (red), the background (blue) and the analysis (black) in the zoomed area [3].
Published: 2017

4. A new hybrid optimization algorithm for variational data assimilation of unsteady wake flows

Author: Gronskis, A., Dominique Heitz, Etienne Mémin, Facultad de Ingeniería [Buenos Aires] (FIUBA), Universidad de Buenos Aires [Buenos Aires] (UBA), Fluid Flow Analysis, Description and Control from Image Sequences (FLUMINANCE), Institut de Recherche Mathématique de Rennes (IRMAR), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Departamento de Física [Universidad de Buenos Aires], Universidad de Buenos Aires [Buenos Aires] (UBA)-Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-INSTITUT AGRO Agrocampus Ouest, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Inria Rennes – Bretagne Atlantique, ANR-11-LABX-0020,LEBESGUE,Centre de Mathématiques Henri Lebesgue : fondements, interactions, applications et Formation(2011), Facultad de Ingenieria [Buenos Aires] ( LFD ), Universidad de Buenos Aires [Buenos Aires], Fluid Flow Analysis, Description and Control from Image Sequences ( FLUMINANCE ), Institut de Recherche Mathématique de Rennes ( IRMAR ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -AGROCAMPUS OUEST-École normale supérieure - Rennes ( ENS Rennes ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National des Sciences Appliquées ( INSA ) -Université de Rennes 2 ( UR2 ), Université de Rennes ( UNIV-RENNES ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Centre National de la Recherche Scientifique ( CNRS ) -Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture ( IRSTEA ) -Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique ( Inria ), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement ( UR OPAALE ), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture ( IRSTEA ), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut de Recherche Mathématique de Rennes (IRMAR), AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-AGROCAMPUS OUEST, Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA), and Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Inria Rennes – Bretagne Atlantique
Subjects: [ INFO.INFO-MO ] Computer Science [cs]/Modeling and Simulation, DATA ASSIMILATION, 4DVAR, WAKE FLOW, [SDE]Environmental Sciences, [ SPI.MECA.MEFL ] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph], TURBULENCE, [ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [SPI.MECA.MEFL]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph]
Abstract: [Departement_IRSTEA]Ecotechnologies [TR1_IRSTEA]SPEE; International audience; In typical variational data assimilation (DA) applications for unsteady flows the search space is large and multidimensional, while prior information about the control vector function is not available. Stochastic optimization algorithms like genetic algorithms (GA) perform global optimization but waste computational effort by doing a random search. On the other hand, deterministic algorithms like gradient descent converge rapidly but may get stuck in local minima of multimodal functions. Here, we present a new hybrid global optimization technique, where a gradient-based local search method is combined with a genetic algorithm to achieve faster convergence and better accuracy of final solution without getting trapped in local minima. The proposed methodology is applied to the reconstruction of unsteady bidimensional flows past a rotationally oscillating cylinder. More precisely, the possibility of reconstructing the rotational speed of the cylinder given observations of a reference flow was investigated via variational DA (Fig. 1). Fig. 1 Temporal mean streamwise velocity field for Reference flow, the observation domain is delineated in white lines. In order to decrease memory and computational time requirements, we used an alternative formulation of the optimization procedure proposed by Tsoulos et al. (2008). This formulation avoids the execution of the local search process each time a local minimum is found progressively by the genetic operations step (Fig. 2-left). Accordingly, the genetic algorithm was first used to approximately locate a good global minimum. Then a gradient based local search was done with the best solution found by the genetic algorithm as its starting point (Fig. 2-right). Thus, the GA was used to go near the vicinity of a good global minima and the gradient descent scheme was used to find the global minimum accurately. This approach is advantageous because it allows for exploration of new regions of the search space while retaining the ability to improve good solutions already found. The stochastic approach utilizes the grammatical evolution (GE) procedure to create trial solutions, while the GA utilizes the operations of crossover and mutation to create the evolving generations. Fig. 2 Typical convergence histories for the Hybrid approach by Tsoulos et al. (2008) (left) and present formulation (right).
Published: 2017

5. Modèle d'observation stochastique pour la mesure du mouvement grand champ

Author: Romain Schuster, Dominique Heitz, Etienne Mémin, Anthony Guibert, Philippe Loisel, Institut Technique des Gaz et de l'Air (ITGA), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Fluid Flow Analysis, Description and Control from Image Sequences (FLUMINANCE), Institut de Recherche Mathématique de Rennes (IRMAR), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-INSTITUT AGRO Agrocampus Ouest, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), ANR-11-LABX-0020,LEBESGUE,Centre de Mathématiques Henri Lebesgue : fondements, interactions, applications et Formation(2011), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Inria Rennes – Bretagne Atlantique, Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS), Institut Technique des Gaz et de l'Air ( ITGA ), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement ( UR OPAALE ), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture ( IRSTEA ), Fluid Flow Analysis, Description and Control from Image Sequences ( FLUMINANCE ), Institut de Recherche Mathématique de Rennes ( IRMAR ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -AGROCAMPUS OUEST-École normale supérieure - Rennes ( ENS Rennes ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National des Sciences Appliquées ( INSA ) -Université de Rennes 2 ( UR2 ), Université de Rennes ( UNIV-RENNES ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Centre National de la Recherche Scientifique ( CNRS ) -Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture ( IRSTEA ) -Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique ( Inria ), AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-AGROCAMPUS OUEST, Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Inria Rennes – Bretagne Atlantique, and Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)
Subjects: [ INFO.INFO-MO ] Computer Science [cs]/Modeling and Simulation, Optical flow estimator, [ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [SPI.MECA.MEFL]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph], PIV, Modélisation stochastique, Particle Image Velocimetry, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.8: Scene Analysis/I.4.8.2: Motion, [ SPI.MECA.MEFL ] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph], Flot optique, ACM : I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.8: Scene Analysis/I.4.8.2: Motion, Turbulence Models, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract: International audience; The PIV characterization of flows on large fields of view requires an adaptation of the motion estima- tion method from image sequences. The backward shift of the camera coupled to a dense scalar seeding involves a large scale observation of the flow, thereby producing uncertainty about the observed pheno- mena. By introducing a stochastic term related to this uncertainty into the observation term, we show in this paper that we can improve the accuracy of the estimated velocity field by optical flow.; La caractéristation PIV d'écoulements sur des champs de grande taille nécessite une adaptation de la méthode d'estimation de mouvement à partir de séquences d'images. L'éloignement de la caméra couplé à un ensemencement dense de type scalaire impliquent une observation grande échelle de l'écoulement, produisant de ce fait une incertitude sur les phenomènes observés. En introduisant dans le modèle d'ob-sevation un terme stochastique lié à cette incertitude, nous montrons dans cet article que nous pouvons améliorer la précision du champ de vitesse estimé par flot optique.
Published: 2017

6. Closed-loop control of a spatially developing free shear flow around a steady state

Author: Anda-Ondo, D., Carlier, Julien, Collewet, C., Optimisation des procédés en Agriculture, Agroalimentaire et Environnement ( UR OPAALE ), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture ( IRSTEA ), Fluid Flow Analysis, Description and Control from Image Sequences ( FLUMINANCE ), Institut de Recherche Mathématique de Rennes ( IRMAR ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -AGROCAMPUS OUEST-École normale supérieure - Rennes ( ENS Rennes ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National des Sciences Appliquées ( INSA ) -Université de Rennes 2 ( UR2 ), Université de Rennes ( UNIV-RENNES ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Centre National de la Recherche Scientifique ( CNRS ) -Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture ( IRSTEA ) -Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique ( Inria ), Région Bretagne, International Federation of Automatic Control, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Fluid Flow Analysis, Description and Control from Image Sequences (FLUMINANCE), Institut de Recherche Mathématique de Rennes (IRMAR), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-INSTITUT AGRO Agrocampus Ouest, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Inria Rennes – Bretagne Atlantique, Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut de Recherche Mathématique de Rennes (IRMAR), AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-AGROCAMPUS OUEST, Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA), ANR-11-LABX-0020,LEBESGUE,Centre de Mathématiques Henri Lebesgue : fondements, interactions, applications et Formation(2011), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Inria Rennes – Bretagne Atlantique, and Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Inria Rennes – Bretagne Atlantique
Subjects: TIME INVARIANT SYSTEM, [PHYS.MECA.MEFL]Physics [physics]/Mechanics [physics]/Mechanics of the fluids [physics.class-ph], [ PHYS.MECA.MEFL ] Physics [physics]/Mechanics [physics]/Mechanics of the fluids [physics.class-ph], OUTPUT FEEDBACK CONTROL, Time-invariant systems, Control of fluid flows and fluids-structures interactions, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Physics::Fluid Dynamics, CONTROL OF FLUID FLOWS, [ SPI.AUTO ] Engineering Sciences [physics]/Automatic, [SDE]Environmental Sciences, FLUID STRUCTURE INTERACTION, [PHYS.MECA.MEFL]Physics [physics]/Mechanics [physics]/Fluid mechanics [physics.class-ph], LINEAR CASE, Output feedback control (linear case)
Abstract: [Departement_IRSTEA]Ecotechnologies [TR1_IRSTEA]SPEE; International audience; This paper provides preliminary results on the closed-loop control of a spatially developing mixing-layer induced by two parallel incident streams with different velocities. The goal of the control law was to stabilize the flow around a desired state (known to reduce mixing). The way to achieve this flow control consists of linearizing the Navier-Stokes equations about the desired state, spatially discretizing the resulting linear system and determining the feedback gain according to an optimal control law. Actuations were located in the input boundary of the system. State of the flow was assumed to be reconstructed from image sensors. The control law has been validated on a realistic non-linear system (Navier-Stokes solver). More precisely, these simulation results have shown that perturbations can be efficiently rejected.
Published: 2017
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7. Identifying cost-competitive greenhouse gas mitigation potential of French agriculture

Author: Nathalie Delame, Marc Benoit, Marie-Hélène Jeuffroy, Sylvain Pellerin, Fabrice Béline, Elisabeth Samson, Melynda Hassouna, Claire Chenu, Stéphane De Cara, Dominic Moran, Catherine Hénault, Denis A. Angers, Philippe Faverdin, Isabelle Savini, Jean-Pierre Butault, Laure Bamière, Lenaïc Pardon, Pierre Dupraz, Aurélie Metay, Philippe Chemineau, Florence Garcia-Launay, Michel Doreau, Katja Klumpp, Caroline Colnenne-David, Sylvie Recous, Interactions Sol Plante Atmosphère (ISPA), Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de la Recherche Agronomique (INRA), Economie Publique (ECO-PUB), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Université Paris-Saclay, Centre de recherche et de développement sur les aliments, Agriculture et Agroalimentaire Canada [Saint Hyacinte, Québec, Canada], Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Unité Mixte de Recherches sur les Herbivores - UMR 1213 (UMRH), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Institut National de la Recherche Agronomique (INRA), Laboratoire d'Economie Forestière (LEF), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), Agronomie, AgroParisTech-Institut National de la Recherche Agronomique (INRA), Structures et Marché Agricoles, Ressources et Territoires (SMART), AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA), Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Sol Agro et hydrosystème Spatialisation (SAS), Unité de recherche Science du Sol (USS), Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), Institut National de la Recherche Agronomique (INRA)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS), Fonctionnement et conduite des systèmes de culture tropicaux et méditerranéens (UMR SYSTEM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier (CIHEAM-IAMM), Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Scotland's Rural College (SCUR), Fractionnement des AgroRessources et Environnement - UMR-A 614 (FARE), Université de Reims Champagne-Ardenne (URCA)-Institut National de la Recherche Agronomique (INRA)-SFR Condorcet, Université de Reims Champagne-Ardenne (URCA)-Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS)-Université de Reims Champagne-Ardenne (URCA)-Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS), Unité Prospective (PROSPECTIVE), Interactions Sol Plante Atmosphère ( ISPA ), Institut National de la Recherche Agronomique ( INRA ) -Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine ( Bordeaux Sciences Agro ), Economie Publique ( ECO-PUB ), Institut National de la Recherche Agronomique ( INRA ) -AgroParisTech, Agriculture et Agroalimentaire Canada, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement ( UR OPAALE ), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture ( IRSTEA ), Unité Mixte de Recherches sur les Herbivores ( UMR 1213 Herbivores ), VetAgro Sup ( VAS ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Institut National de la Recherche Agronomique ( INRA ), Laboratoire d'Economie Forestière ( LEF ), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes ( ECOSYS ), Structures et Marché Agricoles, Ressources et Territoires ( SMART ), Institut National de la Recherche Agronomique ( INRA ) -AGROCAMPUS OUEST, Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] ( PEGASE ), Sol Agro et hydrosystème Spatialisation ( SAS ), Unité de recherche Science du Sol ( USS ), Institut National de la Recherche Agronomique ( INRA ), Unité de Recherche sur l'Ecosystème Prairial, Fonctionnement et conduite des systèmes de culture tropicaux et méditerranéens ( SYSTEM ), Institut National de la Recherche Agronomique ( INRA ) -Centre international d'études supérieures en sciences agronomiques ( Montpellier SupAgro ) -Centre de Coopération Internationale en Recherche Agronomique pour le Développement ( CIRAD ) -Institut national d’études supérieures agronomiques de Montpellier ( Montpellier SupAgro ), Land Economy and Environment Research, SRUC, Fractionnement des AgroRessources et Environnement - UMR-A 614 ( FARE ), SFR Condorcet, Université de Reims Champagne-Ardenne ( URCA ) -Université de Picardie Jules Verne ( UPJV ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Reims Champagne-Ardenne ( URCA ) -Université de Picardie Jules Verne ( UPJV ) -Centre National de la Recherche Scientifique ( CNRS ) -Institut National de la Recherche Agronomique ( INRA ) -Université de Reims Champagne-Ardenne ( URCA ), UAR 1384 Antenne - Délégation à l'Expertise scientifique collective, à la Prospective et aux Etudes, Institut National de la Recherche Agronomique ( INRA ) -Direction Collégiale ( DCOLL ) -Antenne - Délégation à l'Expertise scientifique collective, à la Prospective et aux Etudes ( Antenne - DEPE ), Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Unité Mixte de Recherche sur les Herbivores - UMR 1213 (UMRH), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de la Recherche Agronomique (INRA)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Structures et Marché Agricoles, Ressources et Territoires (SMART-LERECO), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Scotland's Rural College (SRUC), Fractionnement des AgroRessources et Environnement (FARE), Université de Reims Champagne-Ardenne (URCA)-Institut National de la Recherche Agronomique (INRA), Délégation à l'Expertise scientifique collective, à la Prospective et aux Etudes (UAR), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier (CIHEAM-IAMM), and Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)
Subjects: [SDV]Life Sciences [q-bio], Geography, Planning and Development, Biomass, 010501 environmental sciences, Management, Monitoring, Policy and Law, 7. Clean energy, 01 natural sciences, Greenhouse gas, Agricultural economics, 12. Responsible consumption, Marginal abatement costs, Mitigation measures, Economics, Production (economics), 0105 earth and related environmental sciences, 2. Zero hunger, Consumption (economics), Land use, [ SDV ] Life Sciences [q-bio], business.industry, Agriculture, 04 agricultural and veterinary sciences, 15. Life on land, Investment (macroeconomics), 13. Climate action, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Livestock, business
Abstract: The agriculture, forestry and other land use sector are responsible for 24% (10–12 Pg CO2e per year) of anthropogenic greenhouse gas (GHG) emissions worldwide, with concomitant opportunities for mitigation. A scientific panel used deliberative methods to identify ten technical measures comprising 26 sub-measures to reduce GHG emissions from agriculture in France. Their abatement potential and cost are compared. The proposed measures concern nitrogen (N) management, management practices that increase carbon stocks in soils and biomass, livestock diets, and energy production and consumption on farms. Results show that the total abatement potential can be divided into three parts. One third of the cumulated abatement potential corresponds to sub-measures that can be implemented at a negative technical cost. These sub-measures focus on increased efficiency in input use including N fertilisers, animal feed and energy. The second third are sub-measures with moderate cost (€25 per metric Mg of avoided CO2e). These require investment with no direct financial return, the purchase of particular inputs, dedicated labour time or involve production losses. Assuming additivity, the cumulated abatement is 32.3 Tg CO2e per year in 2030, but only 10 Tg (i.e. 10% of current agricultural emissions) when calculated under current inventory rules. This study confirms that a significant abatement potential exists in the agricultural sector, with two thirds of this potential at low or even negative cost. This is likely to be an underestimated as it is based on a status quo of the current agricultural system. Results also emphasise the need to upgrade inventory rules so that efforts to reduce emissions can be accounted for.
Published: 2017
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8. Vers l'assimilation PIV d'écoulements de sillages à grande échelle : étude de modèles sous maille

Author: Pranav Chandramouli, Dominique Heitz, Etienne Mémin, Sylvain Laizet, Fluid Flow Analysis, Description and Control from Image Sequences (FLUMINANCE), Institut de Recherche Mathématique de Rennes (IRMAR), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS), Imperial College London, Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-INSTITUT AGRO Agrocampus Ouest, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Inria Rennes – Bretagne Atlantique, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), ANR-11-LABX-0020,LEBESGUE,Centre de Mathématiques Henri Lebesgue : fondements, interactions, applications et Formation(2011), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), IMPERIAL COLLEGE LONDON DEPARTMENT OF AERONAUTICS LONDON GBR, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-AGROCAMPUS OUEST, Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Inria Rennes – Bretagne Atlantique, Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA), Fluid Flow Analysis, Description and Control from Image Sequences ( FLUMINANCE ), Institut de Recherche Mathématique de Rennes ( IRMAR ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -AGROCAMPUS OUEST-École normale supérieure - Rennes ( ENS Rennes ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National des Sciences Appliquées ( INSA ) -Université de Rennes 2 ( UR2 ), Université de Rennes ( UNIV-RENNES ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Centre National de la Recherche Scientifique ( CNRS ) -Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture ( IRSTEA ) -Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique ( Inria ), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement ( UR OPAALE ), and Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture ( IRSTEA )
Subjects: [ INFO.INFO-MO ] Computer Science [cs]/Modeling and Simulation, SUBGRID MODELLING, SUNGRID TENSOR, DATA ASSIMILATION, LES, [SDE]Environmental Sciences, [ SPI.MECA.MEFL ] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph], [ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, MODELE SUBGRID, [SPI.MECA.MEFL]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph]
Abstract: [Departement_IRSTEA]Ecotechnologies [TR1_IRSTEA]SPEE; International audience; With the increasing attraction of data assimilation combined with improved computational power, the concept of using image based velocity measurements as a guiding mechanism for the numerical simulation of flow dynamics has gained a lot of interest. Previous PIV Data Assimilation study implemented on Incompact3d-a parallelised flow solver developed by [1]-has performed admirably in the case of a DNS of low Reynolds number wake flow [2]. However, performing such data assimilation on a Direct Numerical Simulation (DNS) basis remains computationally unachievable even for flows at moderate Reynolds number. Only, coarse Large Eddy Simulation (LES) is conceivable. This necessitates the identification of the best suited subgrid model for the flow under study, i.e. cylinder wake flow at a Reynolds number of 3900 corresponding to the turbulent Von-Karman vortex shedding regime (see figure 1 left). This is the focus of the present work. Over the past decades, numerous LES sub-grid scale (SGS) models have been proposed each possessing some unique set of advantages. However, there exists no universal model providing statistically accurate results for all types of flows. Several SGS models have been compared. Models under scrutiny include the classical Smagorinsky model along with contemporary models under uncertainty developed by [2] namely Stochastic Smagorinsky (StSmag), Stochastic Spatial (StSp), and Stochastic Temporal (StTe) covariance models. The numerical simulation was performed on a very low-resolution mesh compared to a DNS as well as the LES simulations of [3]. The simulation statistics have been compared with the PIV data of [3] along with an under resolved DNS (URDNS) at the LES resolution mainly to identify the improvements in statistics (see figure 1 right). The statistics clearly show improved fit to the PIV data with the stochastic SGS models as compared to classic Smagorinsky model that over smoothens the velocity gradient– the directional dissipation associated with the stochastic models along with other factors can be attributed to this improvement. The next step will consist to perform a 4DVar PIV assimilation with such SGS models.
Published: 2016

9. Optical Flow Estimation out of Infrared Image Sequences of Biogas

Author: Barbu, Ioana, Guibert, Anthony, Loisel, Philipe, Heitz, Dominique, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Fluid Flow Analysis, Description and Control from Image Sequences (FLUMINANCE), Institut de Recherche Mathématique de Rennes (IRMAR), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-INSTITUT AGRO Agrocampus Ouest, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), ADEME, Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Inria Rennes – Bretagne Atlantique, IRSTEA RENNES UR OPAALE FRA, Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut de Recherche Mathématique de Rennes (IRMAR), AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-AGROCAMPUS OUEST, Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA), ANR-11-LABX-0020,LEBESGUE,Centre de Mathématiques Henri Lebesgue : fondements, interactions, applications et Formation(2011), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement ( UR OPAALE ), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture ( IRSTEA ), Fluid Flow Analysis, Description and Control from Image Sequences ( FLUMINANCE ), Institut de Recherche Mathématique de Rennes ( IRMAR ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -AGROCAMPUS OUEST-École normale supérieure - Rennes ( ENS Rennes ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National des Sciences Appliquées ( INSA ) -Université de Rennes 2 ( UR2 ), Université de Rennes ( UNIV-RENNES ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Centre National de la Recherche Scientifique ( CNRS ) -Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture ( IRSTEA ) -Inria Rennes – Bretagne Atlantique, and Institut National de Recherche en Informatique et en Automatique ( Inria )
Subjects: [ INFO.INFO-MO ] Computer Science [cs]/Modeling and Simulation, BIOGAZ, BIOGAS LEAK, DETECTION DE POLLUTION, leakage, ENERGIE, TRAITEMENT D'IMAGE, Biogas, [ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing, [SPI.MECA.MEFL]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph], optical flow, FUITE, image analysis, Optical flow OF, particle image velocimetry, biogas, gases, PIV particle image velocimetry, IR IMAGE, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, VELOCIMETRIE PAR IMAGE DE PARTICULES, Gas leakage, GAZ, FLUX OPTIQUE, [SDE]Environmental Sciences, [ SPI.MECA.MEFL ] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph], ANALYSEUR INFRAROUGE, Jet flow, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, energy, Methanization bioprocesses
Abstract: International audience; Over the past years, agricultural mechanisation plants have known a steep emergence, encouraged, among other factors, by an estimated high environmental gain. However, the occurrence of the biogas leaks around the installations tends to depreciate the latter. The classical methane loss estimation techniques rely on ballpark figures and numerous simplifying assumptions; as a consequence, they are attached to a loose confidence score. Recently, such leakages have been detected and quantified with infrared (IR) sensors. In particular, optical flow methods have been used to estimate the flow out of the resulting IR image sequences. We address this problem in the current study; more explicitly, we tackle the question of the optical flow estimation out of IR images of biogas. For doing so we i) we build a benchmark mimicking with high-fidelity the outdoor conditions of a real methanisation plant ii) we reconstruct the projected velocity fields of the biogas plume with a technique with uncertainty evaluation iii) we validate our approach by assessing the reconstruction of the gas leakage 2D silhouette out of IR images against instantaneous fields estimated with high accuracy out of particle image velocimetry (PIV) measurements.; Ces dernières années la production d'énergie à partir de biogaz a été encouragée en agriculture. Toutefois des fuites de gaz peuvent se produire sur les installations. Les techniques d'estimations de débits de fuite actuelles sont peu précises. L'objectif est d'exploiter la visualisation infrarouge -déjà utilisée en détection de fuites- pour la mesure des débits de fuites. Pour ce faire on propose un nouvel estimateur de mouvement de gaz à partir de séquences d'images infrarouge.
Published: 2016
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10. Free water surface constructed wetlands limit the dissemination of extended-spectrum beta-lactamase producing Escherichia coli in the natural environment

Author: Géraldine Depret, Catherine Boutin, Alain Hartmann, Stéphanie Prost-Boucle, S. Papias, Anne-Laure Vivant, Christine Ziebal, Anne-Marie Pourcher, Sophie Le Roux, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Université Bretagne Loire (UBL), UR MAEP, Agroécologie [Dijon], Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Université Bourgogne Franche-Comté [COMUE] (UBFC), LYCéE EMILE ZOLA, French National Agency for Water and Aquatic Environments (ONEMA), Biotechnology and Biological Sciences Research Council (BBSRC), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement ( UR OPAALE ), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture ( IRSTEA ), Université Bretagne Loire ( UBL ), Institut National de la Recherche Agronomique ( INRA ) -Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Université Bourgogne Franche-Comté ( UBFC ), Rennes ( LYCéE EMILE ZOLA ), Université de Lille, Sciences Humaines et Sociales, and Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement
Subjects: Veterinary medicine, Environmental Engineering, Antibiotic resistance, [SDV]Life Sciences [q-bio], 0208 environmental biotechnology, Population, Wetland, 02 engineering and technology, 010501 environmental sciences, Biology, 01 natural sciences, beta-Lactamases, Phragmites, Escherichia coli, education, Waste Management and Disposal, Effluent, Escherichia coli Infections, Feces, 0105 earth and related environmental sciences, Water Science and Technology, Civil and Structural Engineering, education.field_of_study, geography, Typha, geography.geographical_feature_category, [ SDV ] Life Sciences [q-bio], Ecology, Tertiary treatment, Ecological Modeling, Water, biochemical phenomena, metabolism, and nutrition, biology.organism_classification, bacterial infections and mycoses, Pollution, 6. Clean water, 020801 environmental engineering, Constructed wetland, Extended-spectrum beta-lactamase, Wastewater, Wetlands, Multilocus Sequence Typing
Abstract: The fates of Escherichia coli and extended-spectrum beta-lactamase-producing E. coli (ESBL E. colt) were studied over a period of one year in a free water surface constructed wetland (FWS CW) with a succession of open water zones and vegetation ponds (Typha or Phragmites), that received the effluent from a wastewater treatment plant. ESBL E. coli were detected and isolated from all sampling areas of the FWS CW throughout the study period. They represented 1 parts per thousand of the total E. colt population regardless of the origin of samples. Two main factors affected the log removal of E. colt and of ESBL E. coli: the season and the presence of vegetation. Between the inlet and the outlet of the FWS CW, the log removal of E. coli ranged from 1.5 in the warmer season (summer and fall) to 3.0 in the colder season (winter and spring). The concentrations of E. coli decreased significantly in the vegetated areas during the colder season, but increased in the warmer season, suggesting an effect of the plant growth stage on the survival of E. colt. Among the 369 ESBL E. coli isolates collected during our study, 84% harbored the CTX-M-ESBL type and 553% carried bla genes on plasmid DNA. Furthermore, 93% of the ESBL E. colt isolates were multidrug resistant but the proportion of resistant strains did not change significantly along the FWS CW. ESBL E. coli were characterized by MLST analysis using the 7 genes based Achtman Scheme. ESBL E. coli isolated from water, sediments, roots and feces of myocastors collected in the FWS CW and in the recipient river were genotypically related, suggesting persistence and circulation of the ESBL producing E. colt throughout the FWS CW and in the receiving river. Overall, these observations show that FWS CW could be an efficient treatment for ESBL E. colt disinfection of wastewater and could limit their dissemination in the aquatic environment.
Published: 2016
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11. Multi-exponential MRI T2 maps: A tool to classify and characterize fruit tissues

Author: Collewet, Guylaine, Musse, Maja, El Hajj, Christian, Moussaoui, Saïd, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire des Sciences du Numérique de Nantes (LS2N), Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-École Centrale de Nantes (Nantes Univ - ECN), Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes université - UFR des Sciences et des Techniques (Nantes univ - UFR ST), Nantes Université - pôle Sciences et technologie, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - pôle Sciences et technologie, and Nantes Université (Nantes Univ)
Subjects: [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], Fruit, Image Processing, Computer-Assisted, Biomedical Engineering, Biophysics, Radiology, Nuclear Medicine and imaging, Magnetic Resonance Imaging, ComputingMilieux_MISCELLANEOUS
Abstract: The estimation of multi-exponential relaxation time T
Published: 2022
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12. Towards numerical simulation of a wind machine during spring frost calibrated with field measurements

Author: Clara Le Cap, Johan Carlier, Marwan Katurji, Dongqi Lin, Hervé Quénol, Philippe Georgeault, Emmanuel Buisson, Dominique Heitz, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Weather Measures, School of Earth and Environment (UWA), The University of Western Australia (UWA), Centre for Atmospheric Research [Christchurch], University of Canterbury [Christchurch], Littoral, Environnement, Télédétection, Géomatique (LETG - Rennes ), Université de Brest (UBO)-Université de Rennes 2 (UR2)-Nantes Université (Nantes Univ)-Littoral, Environnement, Télédétection, Géomatique UMR 6554 (LETG), Université de Brest (UBO)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut de Géographie et d'Aménagement Régional de l'Université de Nantes (Nantes Univ - IGARUN), Nantes Université - pôle Humanités, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - pôle Humanités, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Centre National de la Recherche Scientifique (CNRS)-Institut de Géographie et d'Aménagement Régional de l'Université de Nantes (Nantes Univ - IGARUN), Nantes Université (Nantes Univ), EGU - European Geosciences Union, and European Project: SICTAG
Subjects: [SDE.IE]Environmental Sciences/Environmental Engineering, [SPI.FLUID]Engineering Sciences [physics]/Reactive fluid environment
Abstract: International audience; Spring frost has been recognized as the most harmful weather hazard for agriculture. One way to fight it back is using a wind machine - a 6-m diameter blowing fan atop a 10-m mast. It rotates on itself in approximately 4min30s and blows a slightly positive air using the strength of the nocturnal thermal inversion to mix cold air near the ground with warmer air above. Previous studies have focused on the protection area of the wind machine under different weather conditions or propeller designs. However, while weather conditions are undergone and field measurements are sparse, effects like the topography, the synergy between devices, or the addition of a burner are hard to catch and separate and are, therefore, not yet well understood. In this study, we present field measurements dedicated to the future calibration of a computational fluid dynamics model (PALM) involving an actuator disk to simulate a wind machine operating during radiative frost conditions. This numerical model will aim to understand better such tower's external effects, for which field measurements are challenging to implement. To characterize the jet of the propeller at the onset, vertical profiles were measured with a 3D sonic anemometer at high frequency (100Hz) 10 m away from the wind machine every meter between 3 and 15 m heights. Mass flow and momentum rates of about 500m3/s and 5000N were deduced for some different designs of wind machines. To characterize how the jet interacts with the ground regarding the distance from its source, 2D sonic anemometers were placed in a row in front of the wind machine. Results highlight three different zones where the jet behaved distinctively:- A dead zone, where the jet passed over the ground (0 to 30 m away from the WM);- An impact zone where the jet directly hit the ground with maximum velocity (40 to 60m away from the WM);- A spreading zone where the protection mixing was due to eddies spreading in the inter-rows and breaking into smaller eddies in contact with posts and vine plants (70m away from the WM and beyond). As the distance from the machine increased, the jet velocity decreased before vanishing.From these results about the onset condition and development of the jet, it will be possible to tune the rotating actuator disk to reproduce with PALM (an LES meteorological-oriented modeling system) an acceptable behavior of the flows (gust and weather interacting with the ground) despite several simplifications of the underlying physics. While calibrations are still ongoing, the first results are encouraging, whether it be on a wind machine in a free environment or with the reproduction of a radiative night situation. The primary analysis will focus on the animation of state variables to assist in analyzing statistical results on field measurements. As little knowledge is available about the combined use of a burner with a wind machine, several strategies for a burner location will be tested in order to initiate a research topic that the authors believe is currently unexplored.
Published: 2023
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13. Observation of the microstructure of a bi-extended hydrated dough and hydrated gluten under large strain and extremely low strain-rates: Results of an initial study

Author: Kossigan Bernard Dedey, David Grenier, Laurent Blondel, Yves Diascorn, Marie-Hélène Morel, Tiphaine Lucas, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université de Rennes (UR), Ingénierie des Agro-polymères et Technologies Émergentes (UMR IATE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Montpellier (UM)
Subjects: Rupture, [SDV.IDA]Life Sciences [q-bio]/Food engineering, Rheology, Mechanics, Biochemistry, Food Science, large strain
Abstract: International audience; A small bubble-inflation device was developed for use in conjunction with a Low-to-Mid Range Magnification Digital Microscope. This device made it possible to observe the bi-extension of dough and gluten films at the top of a bubble under conditions that mimicked as closely as possible the typical GCW thicknesses, strains, strain rates and gaseous ambience found in dough during everyday proving or baking. For this stage, experiments were carried out at 20 °C. Stress-strain relationships were measured at strain rates ranging from 0.0006 to 0.09 s−1. The reduction in size yielded higher stress measurements compared to the results obtained from usual inflation devices (Alveograph®). Strain hardening in dough and hydrated gluten was observed regardless of the strain rate applied. A first trial using image analysis of the top of the bubble during deformation revealed useful information on the locations of the dough constituents and made it possible to reevaluate strain and strain-rate. The Hencky strain and stress at rupture were found to be of the order of 1.23 and 50–100 kPa respectively. This work illustrates the potential benefits of linking image analysis to a bubble-inflation device for the analysis of the mechanisms involved in the mechanical rupture of dough films.
Published: 2023
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14. Characterization of Potato Tuber Tissues Using Spatialized MRI T2 Relaxometry

Author: Guylaine Collewet, Saïd Moussaoui, Stephane Quellec, Ghina Hajjar, Laurent Leport, Maja Musse, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), École Centrale de Nantes (Nantes Univ - ECN), Nantes Université (Nantes Univ), Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Université de Rennes (UR)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Rennes Angers, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), and This work is part of the TuberBioScan research project financed by the Brittany Region and FEDER as part of the Innovation Collaborative au Croisement des Filières program.
Subjects: storage, T2, tuber, classification, [SDE]Environmental Sciences, relaxometry, Molecular Biology, Biochemistry, MRI
Abstract: International audience; Magnetic Resonance Imaging is a powerful non-destructive tool in the study of plant tissues. For potato tubers, it greatly assists the study of tissue defects and tissue evolution during storage. This paper describes the MRI analysis of potato tubers with internal defects in their flesh tissue at eight sampling dates from 14 to 33 weeks after harvest. Spatialized multi-exponential T2 relaxometry was used to generate bi-exponential T2 maps, coupled with a classification scheme to identify the different T2 homogeneous zones within the tubers. Six classes with statistically different relaxation parameters were identified at each sampling date, allowing the defects and the pith and cortex tissues to be detected. A further distinction could be made between three constitutive elements within the flesh, revealing the heterogeneity of this particular tissue. Relaxation parameters for each class and their evolution during storage were successfully analyzed. The work demonstrated the value of MRI for detailed non-invasive plant tissue characterization.
Published: 2023
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15. Constrained random diffeomorphisms for data assimilation

Author: Resseguier, Valentin, Zhen, Yicun, Chapron, Bertrand, L@b SCALIAN, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Hohai University, Laboratoire d'Océanographie Physique et Spatiale (LOPS), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS), This work is supported by the ERC project 856408-STUOD and SCALIAN DS., and European Project: 856408,STUOD(2020)
Subjects: [MATH.MATH-PR]Mathematics [math]/Probability [math.PR], [MATH.MATH-MP]Mathematics [math]/Mathematical Physics [math-ph], [MATH.MATH-DG]Mathematics [math]/Differential Geometry [math.DG], [NLIN.NLIN-CD]Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD], stochastic advection by Lie transport, covariance inflation, [PHYS.MECA.MEFL]Physics [physics]/Mechanics [physics]/Fluid mechanics [physics.class-ph], ensemble forecast, location uncertainty, data assimilation
Abstract: We show that both SALT and LU equations can be recovered using a prescribed definition of a random diffeomorphism used to perturb the physical space. However, compared with SALT and LU settings, the proposed perturbation scheme does not directly rely on a particular physics. Hence, the random mapping is more flexible and can be applied to any PDE.
Published: 2023

16. Energy cover crops for biogas production increase soil organic carbon stocks: a modeling approach

Author: Florent Levavasseur, Patrice K. Kouakou, Julie Constantin, Romain Cresson, Fabien Ferchaud, Romain Girault, Vincent Jean‐Baptiste, Hélène Lagrange, Sylvain Marsac, Sylvain Pellerin, Sabine Houot, Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Agroécologie et Intensification Durables des cultures annuelles (UPR AIDA), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Département Performances des systèmes de production et de transformation tropicaux (Cirad-PERSYST), AGroécologie, Innovations, teRritoires (AGIR), Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), INRAE Transfert Environnement [Narbonne], INRAE Transfert, Agrosystèmes et impacts environnementaux carbone-azote (Agro-Impact), Institut National de la Recherche Agronomique (INRA), Transfrontalière BioEcoAgro - UMR 1158 (BioEcoAgro), Université d'Artois (UA)-Université de Liège-Université de Picardie Jules Verne (UPJV)-Université du Littoral Côte d'Opale (ULCO)-Université de Lille-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-JUNIA (JUNIA), Université catholique de Lille (UCL)-Université catholique de Lille (UCL), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Gaz Réseau Distribution France (GRDF), ARVALIS - Institut du végétal [Paris], Interactions Sol Plante Atmosphère (UMR ISPA), Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and This work was funded by GRDF.
Subjects: anaerobic digestion, [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, Renewable Energy, Sustainability and the Environment, Forestry, modeling, cover crop, arable crops, Sys- Metha, AMG, biogas, France, SOC, Waste Management and Disposal, Agronomy and Crop Science
Abstract: International audience; Energy cover crops for biogas production through anaerobic digestion (AD) are inserted between two primary crops. They replace either bare soil or non-harvested cover crops, and their management is usually intensified to produce more biomass. They allow the production of renewable energy as well as diges-tate, used as an organic fertilizer, without directly competing with food produc-tion. Because of the increased biomass production and export and of the return of a digested biomass to the soil, the impact of energy cover crops on soil organic carbon (SOC) is questioned. The objective of this paper was to study the differ-ence in SOC stocks induced by the introduction of energy cover crops for AD coupled with the application of the resulting amount of digestate. We used the AD model Sys- Metha combined with the soil C model AMG to simulate SOC stocks for 13 case studies in France, with scenarios comparing different inter-crop management practices, with or without cover crops, harvested or not. Our results indicated that the higher biomass production of energy cover crops (from 6.7 to 11.1 t DM ha−1) in comparison with nonharvested cover crops (2 t DM ha−1) or bare soil led to higher humified C input (belowground input and digestate), despite the high C fraction exported in AD. This resulted in an increase in SOC stocks in comparison with nonharvested cover crops or bare soil (from 0.01 to 0.12 t C ha−1 year−1 over 30 years). The uncertainties in the model parameters did not modify these results. However, in the case of equal biomass production be-tween energy cover crops and nonharvested cover crops, SOC stocks would be lower with energy cover crops.
Published: 2023
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17. Optimizing resource recovery from wastewater with algae-bacteria membrane reactors

Author: Francesca Casagli, Fabrice Beline, Elena Ficara, Olivier Bernard, Biological control of artificial ecosystems (BIOCORE), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Dipartimento di Ingegneria Civile e Ambientale (DICA), Politecnico di Milano [Milan] (POLIMI), and ADEME Biomsa project. Fondazione Cariplo.
Subjects: General Chemical Engineering, [SDE]Environmental Sciences, Environmental Chemistry, General Chemistry, [MATH]Mathematics [math], Industrial and Manufacturing Engineering
Abstract: International audience; Exploiting the combination of algae and bacteria in High Rate Algal/Bacterial Ponds (HRABP) is an emerging approach for wastewater remediation and resource recovery. In this study, the advantage of adding a solid/liquid separation system to uncouple Hydraulic Retention Time (HRT) and Solid Retention Time (SRT) is explored and quantified. A long-term validated model for HRABP was run to simulate and optimize a system at large scale treating digestate. It is shown that by uncoupling HRT and SRT, adapting the liquid depth and the alkalinity content, the algae productivity increases from 9.0 to 14.5 g m−2 d−1 (for HRT = SRT in the range of 5 to 10 days) to 20.3 g m−2 d−1 (for HRT = 0.2 d and SRT = 2 d). Simulations pointed out that maximizing the algal productivity or the fraction of recovered nitrogen in the algal biomass are conflicting goals that are achieved under different operating conditions. Conditions maximising the algal productivity favour algae and heterotrophic bacteria while algae and nitrifying bacteria dominate the system under those conditions optimizing the efficiency of nitrogen recycling. Finally, increasing the influent alkalinity and adapting the water depth can boost the algal productivity without meeting conditions favourable to N2O emission, opening new perspectives for resource recovery through algal biomass valorisation.
Published: 2023
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18. A simple mass balance tool to predict carbon and nitrogen fluxes in anaerobic digestion systems

Author: R. Affes, V. Moinard, Y. Bareha, J. Buffet, R. Girault, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), and AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: Nitrogen, 020209 energy, Digestate, Phase separation, chemistry.chemical_element, Ecological efficiency, 02 engineering and technology, 010501 environmental sciences, 01 natural sciences, 12. Responsible consumption, Biogas, Anaerobic digestion, 0202 electrical engineering, electronic engineering, information engineering, Anaerobiosis, Waste Management and Disposal, 0105 earth and related environmental sciences, 2. Zero hunger, Modeling, Agriculture, Digestate storage, Biodegradable waste, Pulp and paper industry, Carbon, chemistry, 13. Climate action, Biofuels, Greenhouse gas, [SDE]Environmental Sciences, Environmental science
Abstract: International audience; The increase in anaerobic digestion systems has profoundly affected the waste management of territories, particularly for agricultural systems. Changes in cultural practices and imports of organic waste modify the carbon (C) and nitrogen (N) fluxes on territories where anaerobic digestion is implemented. Successful anaerobic digestion can increase the economic and ecological efficiency of the waste management system. Conversely, poor anaerobic digestion leads to low economic and environmental efficiency due to greenhouse gas emissions and nutrient loss. Modeling the impact of anaerobic digestion on the systems integrating anaerobic digestion can improve the efficiency of these practices. The aim of this study was to develop, analyze, and evaluate a simple mass balance tool able to predict carbon and nitrogen fluxes in anaerobic digestion systems. The tool is composed of an exhaustive substrate database used by three models: (i) an anaerobic digestion model that predicts C and N contents in biogas and digestate; (ii) a phase separation model that predicts C and N content in liquid and solid phase digestates; and (iii) a storage model that predicts C and N content in raw, liquid phase, and solid phase digestates, as well as C and N emissions during storage. Sensitivity analyses were performed on the tool to determine critical inputs. Sensitivity analysis showed that outputs were highly sensitive to their respective inputs and to total inputs of solids. Performance evaluation showed that the tool can provide good quality predictions with R-2 correlations between observation and prediction varying from 0.72 to 0.99 with the best predictions obtained for raw digestate.
Published: 2021
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19. Mean wind flow reconstruction of a high-rise building based on variational data assimilation using sparse pressure measurements

Author: M.Y. Ben Ali, G. Tissot, S. Aguinaga, D. Heitz, E. Mémin, Océan Dynamique Observations Analyse (ODYSSEY), Université de Bretagne Occidentale - UFR Sciences et Techniques (UBO UFR ST), Université de Brest (UBO)-Université de Brest (UBO)-Université de Rennes (UR)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Institut de Recherche Mathématique de Rennes (IRMAR), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut Agro Rennes Angers, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Centre Scientifique et Technique du Bâtiment (CSTB), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), ANR-11-LABX-0020,LEBESGUE,Centre de Mathématiques Henri Lebesgue : fondements, interactions, applications et Formation(2011), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria), Fluid Flow Analysis, Description and Control from Image Sequences (FLUMINANCE), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut de Recherche Mathématique de Rennes (IRMAR), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Institut Agro Rennes Angers, and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Rennes 1 (UR1)
Subjects: Renewable Energy, Sustainability and the Environment, Mechanical Engineering, Data assimilation, [PHYS.MPHY]Physics [physics]/Mathematical Physics [math-ph], Wind flow, Mean flow reconstruction, [PHYS.MECA.MEFL]Physics [physics]/Mechanics [physics]/Fluid mechanics [physics.class-ph], Civil and Structural Engineering, Turbulence modeling, [SPI.MECA.MEFL]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph]
Abstract: International audience; Data assimilation consists in combining a model and measurements in order to estimate the state of the system. In wind engineering, the interest to take advantage of both sources of information is extremely high. As a matter of fact, on the one hand, measurements in wind tunnel experiments are in practice extremely sparse and, on the other hand, stationary numerical models based on Reynolds averaged Navier-Stokes (RANS) fail to predict the time-averaged wake accurately. Variational data assimilation (VDA) techniques are defined as high-dimensional optimisation problems, the solution of which is determined through an adjoint method. In practical applications, where only wall pressure measurements on the building are available, an accurate mean flow reconstruction is very challenging, especially in regions far away from any measurements. In the present paper, spatially distributed forces are considered as a control parameter on the momentum equation or the turbulence closure equations. These forcings are interpreted as corrections brought to the turbulence closure. Consequently, the problem corresponds to a high-dimensional optimisation problem for a spatially distributed variable with sparse pressure measurements. Some guidelines are brought here to perform accurate and physically consistent reconstructions for wind engineering applications. In order to deal as closely as possible with a practical application, this study focuses on the realizable revision of the k − ϵ RANS model applied on a high-rise building wake flow. In particular, some regularisation strategies as well as efficient techniques for control parameter selection and identification are provided. 1
Published: 2022
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20. Limited Transmission of Klebsiella pneumoniae among Humans, Animals, and the Environment in a Caribbean Island, Guadeloupe (French West Indies)

Author: Alexis Dereeper, Gaëlle Gruel, Matthieu Pot, David Couvin, Elodie Barbier, Sylvaine Bastian, Jean-Christophe Bambou, Moana Gelu-Simeon, Séverine Ferdinand, Stéphanie Guyomard-Rabenirina, Virginie Passet, Frederic Martino, Pascal Piveteau, Yann Reynaud, Carla Rodrigues, Pierre-Marie Roger, Xavier Roy, Antoine Talarmin, Benoit Tressieres, Marc Valette, Sylvain Brisse, Sébastien Breurec, Unité Transmission, Réservoir et Diversité des Pathogènes [Pasteur Guadeloupe, France] (TReD-Path), Institut Pasteur de la Guadeloupe, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP), Agroécologie [Dijon], Université de Bourgogne (UB)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Dijon, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), CHU Pointe-à-Pitre/Abymes [Guadeloupe], Agroécologie, génétique et systèmes d’élevage tropicaux (ASSET), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Biodiversité et Epidémiologie des Bactéries pathogènes - Biodiversity and Epidemiology of Bacterial Pathogens, Institut Pasteur [Paris] (IP)-Université Paris Cité (UPCité), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Université des Antilles - UFR des sciences médicales Hyacinthe Bastaraud (UA UFR SM), Université des Antilles (UA), Centre d'Investigation Clinique Antilles-Guyane (CIC - Antilles Guyane), Université des Antilles et de la Guyane (UAG)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pointe-à-Pitre/Abymes [Guadeloupe] -CHU de Fort de France-Centre Hospitalier Andrée Rosemon [Cayenne, Guyane Française], This work was supported by a FEDER grant financed by the European Union and Guadeloupe Region (Programme Opérationnel FEDER-Guadeloupe-Conseil Régional 2014–2020, grant no. 2015-FED-192). Carla Rodrigues was supported financially by the MedVetKlebs project, a component of the One Health European Joint Programme (EJP), which has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement no. 773830, and by a Pasteur-Roux fellowship from the Institut Pasteur., We thank the Plateforme de Microbiologie Mutualisée (P2M) of the Institut Pasteur for Illumina sequencing. We thank all of the students, technicians, and clinicians involved in this work at the Pasteur Institute of Guadeloupe and the University Hospital Center of Guadeloupe., European Project: 2015-FED-192,FEDER-Guadeloupe, and European Project: 773830,H2020-SFS-2017-1,MedVetKlebs (a component of European Joint Programme One Health)(2018)
Subjects: Caribbean, Microbiology (medical), Bacterial Zoonoses, General Immunology and Microbiology, Ecology, Physiology, Swine, Cell Biology, Microbial Sensitivity Tests, beta-Lactamases, Anti-Bacterial Agents, Klebsiella Infections, genomic, Klebsiella pneumoniae, [SDV.MP]Life Sciences [q-bio]/Microbiology and Parasitology, Infectious Diseases, Dogs, ESBL, Drug Resistance, Multiple, Bacterial, Genetics, Animals, Humans, One Health, Guadeloupe
Abstract: International audience; Guadeloupe (French West Indies), a Caribbean island, is an ideal place to study the reservoirs of the Klebsiella pneumoniae species complex (KpSC) and identify the routes of transmission between human and nonhuman sources due to its insularity, small population size, and small area. Here, we report an analysis of 590 biological samples, 546 KpSC isolates, and 331 genome sequences collected between January 2018 and May 2019. The KpSC appears to be common whatever the source. Extended-spectrum-β-lactamase (ESBL)-producing isolates (21.4%) belonged to K. pneumoniae sensu stricto (phylogroup Kp1), and all but one were recovered from the hospital setting. The distribution of species and phylogroups across the different niches was clearly nonrandom, with a distinct separation of Kp1 and Klebsiella variicola (Kp3). The most frequent sequence types (STs) (≥5 isolates) were previously recognized as high-risk multidrug-resistant (MDR) clones, namely, ST17, ST307, ST11, ST147, ST152, and ST45. Only 8 out of the 63 STs (12.7%) associated with human isolates were also found in nonhuman sources. A total of 22 KpSC isolates were defined as hypervirulent: 15 associated with human infections (9.8% of all human isolates), 4 (8.9%) associated with dogs, and 3 (15%) associated with pigs. Most of the human isolates (33.3%) belonged to the globally successful sublineage CG23-I. ST86 was the only clone shared by a human and a nonhuman (dog) source. Our work shows the limited transmission of KpSC isolates between human and nonhuman sources and points to the hospital setting as a cornerstone of the spread of MDR clones and antibiotic resistance genes.IMPORTANCE In this study, we characterized the presence and genomic features of isolates of the Klebsiella pneumoniae species complex (KpSC) from human and nonhuman sources in Guadeloupe (French West Indies) in order to identify the reservoirs and routes of transmission. This is the first study in an island environment, an ideal setting that limits the contribution of external imports. Our data showed the limited transmission of KpSC isolates between the different compartments. In contrast, we identified the hospital setting as the epicenter of antibiotic resistance due to the nosocomial spread of successful multidrug-resistant (MDR) K. pneumoniae clones and antibiotic resistance genes. Ecological barriers and/or limited exposure may restrict spread from the hospital setting to other reservoirs and vice versa. These results highlight the need for control strategies focused on health care centers, using genomic surveillance to limit the spread, particularly of high-risk clones, of this important group of MDR pathogens.
Published: 2022
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21. Changes in winter oilseed rape leaf water status monitored by low-field NMR Relaxometry during severe drought

Author: Boulc'H, Pierre-Nicolas, Musse, Maja, Leport, Laurent, Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Université de Rennes (UR)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Rennes Angers, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Musse, Maja
Subjects: [PHYS]Physics [physics], [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, [SDV.BV] Life Sciences [q-bio]/Vegetal Biology, [PHYS] Physics [physics]
Abstract: International audience
Published: 2022

22. Tissue characterization of potato tubers using localized MRI T2 Relaxometry

Author: Collewet, Guylaine, Hajjar, Ghina, Quellec, Stephane, Moussaoui, Saïd, Challois, Sylvain, Deleu, Carole, Leport, Laurent, Musse, Maja, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de Recherche en Communications et en Cybernétique de Nantes (IRCCyN), Mines Nantes (Mines Nantes)-École Centrale de Nantes (ECN)-Ecole Polytechnique de l'Université de Nantes (EPUN), Université de Nantes (UN)-Université de Nantes (UN)-PRES Université Nantes Angers Le Mans (UNAM)-Centre National de la Recherche Scientifique (CNRS), Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Université de Rennes (UR)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Rennes Angers, and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)
Subjects: relaxation transversale, [PHYS.PHYS]Physics [physics]/Physics [physics], pomme de terre, plante, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, IRM
Abstract: International audience
Published: 2022

23. Temperature spatial variability analysis in the aim of enhancing the use or implementation of wind machines park

Author: Le Cap, Clara, Carlier, Johan, Quénol, Hervé, Heitz, Dominique, Buisson, Emmanuel, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Weather Measures, Littoral, Environnement, Télédétection, Géomatique UMR 6554 (LETG), Université de Brest (UBO)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut de Géographie et d'Aménagement Régional de l'Université de Nantes (Nantes Univ - IGARUN), Nantes Université - pôle Humanités, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - pôle Humanités, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ), Europe - EPI Agri - Rural development 2014-2020 for Operational Groups (in the sense of Art 56 of Reg.1305/2013), SICTAG, and European Project: SICTAG
Subjects: [SDE.MCG]Environmental Sciences/Global Changes, Spring frost, [PHYS.MECA.MEFL]Physics [physics]/Mechanics [physics]/Fluid mechanics [physics.class-ph], vineyard, wind machine
Abstract: Spring frosts after budburst are responsible for crop losses and threaten local economies. As global warming tends to advance the phenological stages of plants, these become more and more subject to facing a long period of freezing temperatures. For a given meteorologic situation, the topography of the studied site and the nature of the soil of the plots constituting it, a temperature spatial variability expands within the same territory. Considering a radiative frost, the temperature can thus differ by several degrees, creating areas of cold and warm air that it is necessary to know to fight wisely against the frost. Nowadays, many solutions exist to fight against frost, including the wind machines that dot the Quincy vineyard in France. Weather variables, topographic parameters, and daily minimum temperatures from a network of connected sensors scattered throughout the vineyard are retrieved for the last three spring seasons of 2020,2021, and 2022. Then, thanks to a hierarchical clustering algorithm, it is possible to link the spatial variability of temperatures to the synoptic situation and the topography of the domain. The outcome is the assessment of the frost risk areas to propose a judicious implantation of wind machines in the vineyard of Quincy.
Published: 2022
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24. Characterization of the effects of water shortage on four potato varieties by NMR techniques

Author: Gouerou, Maverick, Pétard, Jonas, Musse, Maja, Quellec, Stephane, Challois, Sylvain, Leconte, Patrick, Val, Florence, Deleu, Carole, Dupuis, Brice, Leport, Laurent, Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Université de Rennes (UR)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Rennes Angers, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Agroscope, Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), and Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, [PHYS]Physics [physics]
Abstract: International audience
Published: 2022

25. Characterization of the effects of water shortage on potato plant

Author: Hajjar, Ghina, Musse, Maja, Quellec, Stephane, Challois, Sylvain, Billiot, Bastien, Jamois, Franck, Barbari, Arnaud, Leconte, Patrick, Langrume, Christophe, Deleu, Carole, Joly, Gisele, Leport, Laurent, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre Mondial de l'Innovation Roullier, Groupe Roullier, Comité Nord Plants de Pommes de Terre, Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Université de Rennes (UR)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Rennes Angers, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Germicopa, and Musse, Maja
Subjects: [PHYS]Physics [physics], [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, [SDV.SA] Life Sciences [q-bio]/Agricultural sciences, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, [SDV.BV] Life Sciences [q-bio]/Vegetal Biology, [PHYS] Physics [physics]
Abstract: International audience
Published: 2022

26. In Vitro Evolution of Listeria monocytogenes Reveals Selective Pressure for Loss of SigB and AgrA Function at Different Incubation Temperatures

Author: Duarte N. Guerreiro, Jialun Wu, Emma McDermott, Dominique Garmyn, Peter Dockery, Aoife Boyd, Pascal Piveteau, Conor P. O’Byrne, Clinical Science Institute, National University of Ireland Galway, National University of Ireland [Galway] (NUI Galway), Agroécologie [Dijon], Université de Bourgogne (UB)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Dijon, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Centre for Microscopy and Imaging - CMI [Galway, Ireland], Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), This project has received funding from the European Union’s Horizon 2020 researchand-innovation program under Marie Skłodowska-Curie grant agreement no. 721456. JialunWu was funded by the Department of Agriculture, Food and the Marine (17/F/244)., and European Project: 721456
Subjects: in vitro evolution, Ecology, sigma(B), general stress response, [SDV]Life Sciences [q-bio], quorum sensing, Genetics and Molecular Biology, bacterial competition, agr system, Listeria monocytogenes, Applied Microbiology and Biotechnology, Food Science, Biotechnology
Abstract: The alternative sigma factor B (σ(B)) contributes to the stress tolerance of the foodborne pathogen Listeria monocytogenes by upregulating the general stress response. We previously showed that σ(B) loss-of-function mutations arise frequently in strains of L. monocytogenes and suggested that mild stresses might favor the selection of such mutations. In this study, we performed in vitro evolution experiments (IVEE) where L. monocytogenes was allowed to evolve over 30 days at elevated (42°C) or lower (30°C) incubation temperatures. Isolates purified throughout the IVEE revealed the emergence of sigB operon mutations at 42°C. However, at 30°C, independent alleles in the agr locus arose, resulting in the inactivation of Agr quorum sensing. Colonies of both sigB mutants and agr mutants exhibited a greyer coloration on 7-days-old agar plates than those of the parental strain. Scanning electron microscopy revealed a more complex colony architecture in the wild type than in the mutant strains. sigB mutant strains outcompeted the parental strain at 42°C but not at 30°C, while agr mutant strains showed a small increase in competitive fitness at 30°C. Analysis of 40,080 L. monocytogenes publicly available genome sequences revealed a high occurrence rate of premature stop codons in both the sigB and agrCA loci. An analysis of a local L. monocytogenes strain collection revealed 5 out of 168 strains carrying agrCA alleles. Our results suggest that the loss of σ(B) or Agr confer an increased competitive fitness in some specific conditions and this likely contributes to the emergence of these alleles in strains of L. monocytogenes. IMPORTANCE To withstand environmental aggressions, L. monocytogenes upregulates a large regulon through the action of the alternative sigma factor B (σ(B)). However, σ(B) becomes detrimental for L. monocytogenes growth under mild stresses, which confer a competitive advantage to σ(B) loss-of-function alleles. Temperatures of 42°C, a mild stress, are often employed in mutagenesis protocols of L. monocytogenes and promote the emergence of σ(B) loss-of-function alleles in the sigB operon. In contrast, lower temperatures of 30°C promote the emergence of Agr loss-of-function alleles, a cell-cell communication mechanism in L. monocytogenes. Our findings demonstrate that loss-of-function alleles emerge spontaneously in laboratory-grown strains. These alleles rise in the population as a consequence of the trade-off between growth and survival imposed by the activation of σ(B) in L. monocytogenes. Additionally, our results demonstrate the importance of identifying unwanted hitchhiker mutations in newly constructed mutant strains.
Published: 2022
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27. Listeria monocytogenes: Investigation of Fitness in Soil Does Not Support the Relevance of Ecotypes

Author: Yann Sévellec, Eliette Ascencio, Pierre-Emmanuel Douarre, Benjamin Félix, Laurent Gal, Dominique Garmyn, Laurent Guillier, Pascal Piveteau, Sophie Roussel, Laboratoire de sécurité des aliments de Maisons-Alfort (LSAl), Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES), Agroécologie [Dijon], Université de Bourgogne (UB)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Dijon, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Direction de l'Evaluation des Risques (DER), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and European Project: 773830, H2020-SFS-2017-1 ,One Health EJP(2018)
Subjects: Microbiology (medical), clonal complex, ecotype, strain origin, [SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study, MESH: Listeria monocytogenes, Listeria monocytogenes, genome-wide-association study, survival, Microbiology, fitness, soil, MESH: Soil, MESH: Listeriosis, [SDV.BBM]Life Sciences [q-bio]/Biochemistry, Molecular Biology, MESH: Foodborne Diseases
Abstract: Listeria monocytogenes (Lm) is a ubiquitous bacterium that causes the serious foodborne illness listeriosis. Although soil is a primary reservoir and a central habitat for Lm, little information is available on the genetic features underlying the fitness of Lm strains in this complex habitat. The aim of this study was to identify (i) correlations between the strains fitness in soil, their origin and their phylogenetic position (ii) identify genetic markers allowing Lm to survive in the soil. To this end, we assembled a balanced panel of 216 Lm strains isolated from three major ecological compartments (outdoor environment, animal hosts, and food) and from 33 clonal complexes occurring worldwide. The ability of the 216 strains to survive in soil was tested phenotypically. Hierarchical clustering identified three phenotypic groups according to the survival rate (SR): phenotype 1 “poor survivors” (SR < 2%), phenotype 2 “moderate survivors” (2% < SR < 5%) and phenotype 3 “good survivors” (SR > 5%). Survival in soil depended neither on strains’ origin nor on their phylogenetic position. Genome-wide-association studies demonstrated that a greater number of genes specifically associated with a good survival in soil was found in lineage II strains (57 genes) than in lineage I strains (28 genes). Soil fitness was mainly associated with variations in genes (i) coding membrane proteins, transcription regulators, and stress resistance genes in both lineages (ii) coding proteins related to motility and (iii) of the category “phage-related genes.” The cumulative effect of these small genomic variations resulted in significant increase of soil fitness.
Published: 2022
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28. MRI method to evaluate effects of water stress on potato tubers during growing

Author: Hajjar, G., Quellec, S., Challois, S., Leconte, Patrick, Deleu, Carole, Joly, Gisèle, Leport, Laurent, Musse, Maja, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Université de Rennes (UR)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Rennes Angers, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), and Germicopa
Subjects: [SDE]Environmental Sciences
Abstract: [Departement_IRSTEA]Ecotechnologies [TR1_IRSTEA]TED [ADD1_IRSTEA]Sûreté alimentaire; International audience; Drought is a major problem affecting agricultural practices as a result of global warming. Potato is considered as a drought sensitive crop, which results in loss of yield and tuber quality. Further, water shortage may induce physiological disorders such as glassy tubers and internal rust spots. Potato response to drought is complex: it depends on cultivar, climatic and soil conditions and water stress timing within the growing period. Characterization of plant adaptive responses is a major issue in the field of phenotyping. There is therefore a demand for the emergence of analytical techniques that are non-invasive, allowing better performance of this phenotyping.In the current work, MRI was used to evaluate the effects of water stress on potato tubers by in situ monitoring of tubers growth kinetics during an eight-week period. In this respect, potato plants were cultivated in pots under controlled and stressed conditions. In the latter case, irrigation was monitored in a way to simulate cultivation of potatoes during drought seasons. The stress experienced by plant was evaluated through the monitoring of soil water potential and soil humidity. 3D morphological images of the underground part of the potato plant in pots were recorded on a 1.5 T MRI scanner (Avanto, Siemens) using a fast spin echo sequence (Fig. 1). The objectives were i) to evaluate the effect of water stress on the individual growth kinetics of tubers and ii) to detect the stage at which rust spots appear and monitor their evolution until harvest.The approaches developed in the present study were shown to be effective to characterize tuber development and quality, providing a quantitative analysis of morphological features of tubers. The results were discussed from the perspective of applying this methodology for phenotyping of plant under water shortage.
Published: 2022

29. Qualification d'un dispositif de gonflage de bulle de pâte de petite taille : étanchéité aux gaz,homogénéité de température, effet du temps initialement laissé à la pâte pour se détendreet analyse de sensibilité numérique de la contrainte-déformation à la valeur initialede diamètre et d'épaisseur du disque de pâte

Author: Dedey, Kossigan Bernard, Grenier, David, Blondel, Laurent, Diascorn, Yves, Lejeune, Antoine, Lucas, Tiphaine, Université de Rennes (UR), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Société d'Accélération du Transfert de Technologies (SATT OUEST VALORISATION), Inrae - UR OPAALE, and Grenier, David
Subjects: [SDV.IDA]Life Sciences [q-bio]/Food engineering, [SDV.IDA] Life Sciences [q-bio]/Food engineering
Abstract: The present work aimed at reinforcing the mechanical results obtained using a home-made and small-sizedbubble inflation device which makes the inflation of thin dough films possible under controlled temperature andatmosphere in a wide range of constant strain rates. The analysis of the experimental biases associated to thatnew small-sized bubble inflation device was carried out. Without inflating bubble, a first part of the work wasdevoted to the analysis of gas tightness of the device at 20°C and 70°C and to the uniformity in temperatureafter stabilization at 70°C. In a second part, bubble inflation experiments were carried out and an experimentalstress-strain sensitivity analysis to the time left for the dough film to relax its stress before bubble inflation aswell as to the initial geometry of the dough disk (diameter and thickness) was conducted. Finally, a numericalsensitivity analysis was performed on the basis of the set of the analytical equations available for the calculationof the height and the radius of the bubble during inflation, as well as for the calculation of the thickness of thedough film, strain and stress at the top of the bubble. The equations developed by Bloksma (1957) and revisedby Charalambides et al. (2006) were adapted to reach constant strain rate at the top of the bubble.
Published: 2022

30. A Two-Stage Biogas Desulfurization Process Using Cellular Concrete Filtration and an Anoxic Biotrickling Filter

Author: Morgane Poser, Luis Rodolfo Duarte E. Silva, Pascal Peu, Éric Dumont, Annabelle Couvert, Institut des Sciences Chimiques de Rennes (ISCR), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Ecole Nationale Supérieure de Chimie de Rennes (ENSCR)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de génie des procédés - environnement - agroalimentaire (GEPEA), École nationale vétérinaire, agroalimentaire et de l'alimentation Nantes-Atlantique (ONIRIS)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Nantes université - UFR des Sciences et des Techniques (Nantes univ - UFR ST), Nantes Université - pôle Sciences et technologie, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - pôle Sciences et technologie, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - Institut Universitaire de Technologie Saint-Nazaire (Nantes Univ - IUT Saint-Nazaire), Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut Universitaire de Technologie - Nantes (Nantes Univ - IUT Nantes), Traitement Eau Air Métrologie (GEPEA-TEAM), Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-École nationale vétérinaire, agroalimentaire et de l'alimentation Nantes-Atlantique (ONIRIS)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), and This research was funded by the French governmental agency ADEME (N°TEZ19-041) and the Region of Brittany (N°1169).
Subjects: Control and Optimization, cellular concrete, Renewable Energy, Sustainability and the Environment, H2S, [SDE.IE]Environmental Sciences/Environmental Engineering, Energy Engineering and Power Technology, desulfurization, biogas, [SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering, biotrickling filter, Electrical and Electronic Engineering, Engineering (miscellaneous), Energy (miscellaneous)
Abstract: A two-stage desulfurization process including an abiotic filtration using cellular concrete waste (first stage) and an anoxic biotrickling filter filling with an inoculated expanded schist material (second stage) was investigated to remove H2S in mimic biogas with limited O2 amount (ranged from 0.5 to 0.8%). The two-stage process was able to satisfactorily remove H2S for all experimental conditions (RE > 97%; H2S concentration = 1500 mg m−3; total Empty Bed Residence Time (EBRT) = 200 s; removal capacity (RC) = 26 g m−3 h−1). Moreover, at a total EBRT = 360 s (i.e., 180 s for each stage), the H2S loading rate (LR) was almost treated by the bed of cellular concrete alone, indicating that abiotic filtration could be applied to satisfactorily remove H2S contained in the gas. According to the H2S concentration entering the biotrickling filter, the majority end-product was either elemental sulfur (S0) or sulfate (SO42−). Thus, the ability of the abiotic filter to remove a significant part of H2S would avoid the clogging of the biotrickling filter due to the deposit of S0. Consequently, this two-stage desulfurization process is a promising technology for efficient and economical biogas cleaning adapted to biogas containing limited O2 amounts, such as landfill biogas.
Published: 2022
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31. Environmental contamination in a high-income country (France) by antibiotics, antibiotic-resistant bacteria, and antibiotic resistance genes: Status and possible causes

Author: Marisa Haenni, Christophe Dagot, Olivier Chesneau, Delphine Bibbal, Jérôme Labanowski, Michèle Vialette, Damien Bouchard, Fabrice Martin-Laurent, Louisiane Calsat, Sylvie Nazaret, Fabienne Petit, Anne-Marie Pourcher, Anne Togola, Morgane Bachelot, Edward Topp, Didier Hocquet, Laboratoire de Lyon [ANSES], Université de Lyon-Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES), Anti-infectieux : supports moléculaires des résistances et innovations thérapeutiques (RESINFIT), CHU Limoges-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Génomique, Environnement, Immunité, Santé, Thérapeutique (GEIST), Université de Limoges (UNILIM)-Université de Limoges (UNILIM), Collection de l'Institut Pasteur (CIP), Institut Pasteur [Paris] (IP)-Université Paris Cité (UPCité), Innovations Thérapeutiques et Résistances (InTheRes), Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de Chimie des Milieux et Matériaux de Poitiers (IC2MP), Université de Poitiers-Institut national des sciences de l'Univers (INSU - CNRS)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP), Anses ANMV (Anses ANMV), Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES), Agroécologie [Dijon], Université de Bourgogne (UB)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Dijon, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Direction de l'Evaluation des Risques (DER), Laboratoire d'Ecologie Microbienne - UMR 5557 (LEM), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Ecole Nationale Vétérinaire de Lyon (ENVL)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Morphodynamique Continentale et Côtière (M2C), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS), Milieux Environnementaux, Transferts et Interactions dans les hydrosystèmes et les Sols (METIS), École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Bureau de Recherches Géologiques et Minières (BRGM) (BRGM), Agriculture and Agri-Food Canada, Saskatoon Research Centre, Agriculture and Agri-Food (AAFC), University of Western Ontario (UWO), Laboratoire Chrono-environnement (UMR 6249) (LCE), Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), Centre Hospitalier Régional Universitaire de Besançon (CHRU Besançon), This document was prepared thanks to the collective expert assessment, carried out by the Anses expert working group ‘Antimicrobial resistance and the environment’ (ANSES opinion 2016-SA-0252), chaired by Morgane Bachelot and whose active contributors are co-authors of this publication., Togola, Anne, Institut Pasteur [Paris], AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Université de Rouen Normandie (UNIROUEN), Normandie Université (NU), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Agriculture and Agri-Food [Ottawa] (AAFC), Laboratoire Chrono-environnement - CNRS - UBFC (UMR 6249) (LCE), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Agence nationale du médicament vétérinaire (ANMV), and École Pratique des Hautes Études (EPHE)
Subjects: [SDE] Environmental Sciences, MESH: Drug Resistance, Microbial, Antibiotic resistance, MESH: One Health, 010501 environmental sciences, Wastewater, 01 natural sciences, MESH: Waste Water, 03 medical and health sciences, Rivers, MESH: Anti-Bacterial Agents, Drug Resistance, Bacterial, Animals, GE1-350, One Health, 030304 developmental biology, 0105 earth and related environmental sciences, General Environmental Science, Environmental antibiotic concentrations, 0303 health sciences, Bacteria, Aquatic environment, [SDV.EE.IEO] Life Sciences [q-bio]/Ecology, environment/Symbiosis, 6. Clean water, Anti-Bacterial Agents, 3. Good health, Environmental sciences, [SDE.BE] Environmental Sciences/Biodiversity and Ecology, Terrestrial environment, 13. Climate action, [SDE]Environmental Sciences, Organic waste product, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, [CHIM.OTHE]Chemical Sciences/Other, [SDV.EE.IEO]Life Sciences [q-bio]/Ecology, environment/Symbiosis
Abstract: This document was prepared thanks to the collective expert assessment, carried out by the Anses expert working group ‘Antimicrobial resistance and the environment’ (ANSES opinion 2016-SA-0252), chaired by Morgane Bachelot and whose active contributors are co-authors of this publication.; International audience; Antimicrobial resistance (AMR) is a major global public health concern, shared by a large number of human and animal health actors. Within the framework of a One Health approach, actions should be implemented in the environmental realm, as well as the human and animal realms. The Government of France commissioned a report to provide policy and decision makers with an evidential basis for recommending or taking future actions to mitigate AMR in the environment. We first examined the mechanisms that underlie the emergence and persistence of antimicrobial resistance in the environment. This report drew up an inventory of the contamination of aquatic and terrestrial environments by AMR and antibiotics, anticipating that the findings will be representative of some other high-income countries. Effluents of wastewater treatment plants were identified as the major source of contamination on French territory, with spreading of organic waste products as a more diffuse and incidental contamination of aquatic environments. A limitation of this review is the heterogeneity of available data in space and time, as well as the lack of data for certain sources.Comparing the French Measured Environmental Concentrations (MECs) with predicted no effect concentrations (PNECs), fluoroquinolones and trimethoprim were identified as representing high and medium risk of favoring the selection of resistant bacteria in treated wastewater and in the most contaminated rivers. All other antibiotic molecules analyzed (erythromycin, clarithromycin, azithromycin, tetracycline) were at low risk of resistance selection in those environments. However, the heterogeneity of the data available impairs their full exploitation. Consequently, we listed indicators to survey AMR and antibiotics in the environment and recommended the harmonization of sampling strategies and endpoints for analyses.Finally, the objectives and methods used for the present work could comprise a useful example for how national authorities of countries sharing common socio-geographic characteristics with France could seek to better understand and define the environmental dimension of AMR in their particular settings.
Published: 2022
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32. Short-term impact of biogas digestates on soils microbial communities

Author: Sadet-Bourgeteau, Sophie, Vautrin, Florian, Piveteau, Pascal, Cannavacciuolo, M, Barré, P, Chauvin, C, Villenave, C, Cluzeau, D, Hoeffner, Kevin, Mulliez, P, Jean-Baptiste, V, Vrignaud, G, Tripied, Julie, Dequiedt, Samuel, Maron, Pierre-Alain, Ranjard, Lionel, EL Mjiyad, Noureddine, Agroécologie [Dijon], Université de Bourgogne (UB)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Dijon, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Légumineuses, Ecophysiologie Végétale, Agroécologie (LEVA), Ecole supérieure d'Agricultures d'Angers (ESA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire de géologie de l'ENS (LGENS), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Elisol Environnement, Ecosystèmes, biodiversité, évolution [Rennes] (ECOBIO), Université de Rennes (UR)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS), Chambre Régionale d'Agriculture des Pays de la Loire, Gaz Réseau Distribution France (GRDF), and ACE METHANISATION
Subjects: high throughput DNA sequencing, [SDV] Life Sciences [q-bio], microcosm experiment, soil microbes, [SDV]Life Sciences [q-bio], organic fertilization
Abstract: International audience; Anaerobic digestion of organic waste is considered a key process to produce renewable energy to meet the growing sustainable energy demand. Digestates can be used in agriculture as soil amendments and improve crop yields. However, their use at large scale in agricultural fields still requires to prove their innocuity on soil biota, especially on microorganisms that play important roles in soil ecosystem. Here, we designed a microcosm experiment to compare the short-term (42-days) effects of four different digestates (derived from cattle manure, energy crop, food residues or slurry with bio-waste) on the soil microbial communities. Each digestate was applied on three contrasting soils representing a range of physicochemical characteristics (BOU, silty clay loam texture; PDL, loam texture and PACA, sandy loam texture). These soils are termed BOU, PDL and PACA hereafter, respectively. None of them had a historical record of digestate application; BOU and PDL were under annual cropping systems, while PACA was a vineyard soil. In addition, selected soils had never received digestates inputs before. Amended microcosms were compared to a control (undigested cattle manure). The effect of digestate inputs on the soil microbial communities was assessed using molecular DNA-based tools (quantification of extracted soil DNA and high-throughput sequencing) to measure microbial biomass and diversity, respectively. The impact of the digestates depended on the soil type. No digestate significantly affected the microbial biomass or diversity of the soil presenting the highest organic matter content (P > 0.05), as compared to the cattle manure. In the other soils, digestate addition led to lower microbial biomass compared to undigested manure. The intensity of this effect was dependent on the digestate type, and so were the microbial diversity indicators. Our results show that 42 days after biogas residue application, the effect of digestates on the soil microbial community structure depends on both the soil type and the digestate characteristics. To summarized, our results suggest that the soil microbial communities of coarse-textured soils with an acidic pH and a low C/N ratio are more sensitive to nitrogen-rich digestate inputs.
Published: 2022

33. A European-wide dataset to uncover adaptive traits of Listeria monocytogenes to diverse ecological niches

Author: Korkealä, Hannu J., Karpíšková, Renáta, Gareis, Manfred, Ruppitsch, W., Hurtado, Ana, Lindström, Miia K., Guillier, Laurent, Cammà, Cesare, Hébraud, Michel, Blanchard, Yannick, Pomilio, Francesco, Gelbíčová, Tereza, Roussel, Sophie, Piveteau, Pascal, Bridier, Arnaud, Pietzka, Ariane Tatjana, Soumet, Christophe, Félix, Benjamin, Torresi, Marina, Radomski, Nicolas, Seyfarth, Anne Mette, Skjerdal, Taran, Wullings, Bart A., Di Pasquale, Adriano, Papić, Bojan, Douarre, Pierre Emmanuel, Felten, Arnaud, Mallet, Ludovic V., Palma, Federica, Szymczak, Barbara, Kramarenko, Toomas, Sévellec, Yann, Šteingolde, Žanete, Leroux, Aurélie, Castro, Hanna, Bulawová, Hana, Oswaldi, Verena, Cabanová, Lenka, Ascensio, Eliette, Canelhas, Monica Ricão, Leblanc, Jean Charles, Marti, Elisabet, Food Hygiene and Environmental Health, Departments of Faculty of Veterinary Medicine, University of Helsinki, Helsinki One Health (HOH), Laboratoire de sécurité des aliments de Maisons-Alfort (LSAl), Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES), Laboratoire de Ploufragan-Plouzané-Niort [ANSES], Laboratoire de Fougères - ANSES, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Agroécologie [Dijon], Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Microbiologie Environnement Digestif Santé (MEDIS), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), Veterinary Research Institute [Brno] (VRI), Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise Guiseppe Caporale (IZSAM), Partenaires INRAE, Norwegian Veterinary Institute [Oslo], Austrian Agency for Health and Food Safety (AGES), Swedish Food Agency, University of Ljubljana, Neiker-Instituto Vasco de Investigación y Desarrollo Agrario (SPAIN), Instituto Vasco de Investigación y Desarrollo Agrario [Derio] (NEIKER), Basque Research and Technology Alliance (BRTA), Wageningen Food Safety Research, Wageningen (WFSR), State Veterinary Institute (SVU), Department of Food Hygiene and Environmental Health [Helsinki], Faculty of Veterinary Medicine [Helsinki], Helsingin yliopisto = Helsingfors universitet = University of Helsinki-Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Institute of Food Safety, Animal Health and Environment (BIOR), Veterinary and Food Laboratory, 51006 Tartu, Estonia, Department of Molecular Biology and Epizootiology, Veterinary and Food Institute in Dolny Kubin, State Veterinary and Food Institute, NRL for Honeybee Health, 026 01 Dolny Kubin, Slovakia, West Pomeranian University of Technology Szczecin, Ludwig Maximilian University [Munich] (LMU), Freie Universität Berlin, Agroscope, National Food Institute [Lyngby] (Forside), and European Project: 773830, H2020-SFS-2017-1 ,One Health EJP(2018)
Subjects: ecological niches, 600 Technik, Medizin, angewandte Wissenschaften::630 Landwirtschaft::630 Landwirtschaft und verwandte Bereiche, Moleculaire Biologie & AMR, MESH: Listeria monocytogenes, 413 Veterinary science, Molecular Biology & AMR, génétique, Foodborne Diseases, Bacterial genetics, dataset, Listeriosis, bacteria, bactérie, transmission, Computer Science Applications, CONTAMINATION, [SDV.MP]Life Sciences [q-bio]/Microbiology and Parasitology, épidémiologie, epidemiology, Statistics, Probability and Uncertainty, niches écologiques, Information Systems, Statistics and Probability, food-borne pathogen, Library and Information Sciences, écosystème, Education, Micro 3: Knowledge and Expertise, SDG 3 - Good Health and Well-being, Team Bacteriology, données de la recherche, Life Science, Animals, Team Bacteriologie, human, microbiologie, SDG 2 - Zero Hunger, sécurité des aliments, MESH: Foodborne Diseases, Ecosystem, Team Bacteriologie, Moleculaire Biologie & AMR, [SDV.GEN.GPO]Life Sciences [q-bio]/Genetics/Populations and Evolution [q-bio.PE], Team Bacteriology, Molecular Biology & AMR, STRAINS, microbiology, fungi, Bacteriology, [SDV.MP.BAC]Life Sciences [q-bio]/Microbiology and Parasitology/Bacteriology, Listeria monocytogenes, SOIL, MESH: Listeriosis, PORK, genetic, humain, Micro 3: Kennis en Expertise, pathogène alimentaire, CLONES
Abstract: Listeria monocytogenes (Lm) is a ubiquitous bacterium that causes listeriosis, a serious foodborne illness. In the nature-to-human transmission route, Lm can prosper in various ecological niches. Soil and decaying organic matter are its primary reservoirs. Certain clonal complexes (CCs) are over-represented in food production and represent a challenge to food safety. To gain new understanding of Lm adaptation mechanisms in food, the genetic background of strains found in animals and environment should be investigated in comparison to that of food strains. Twenty-one partners, including food, environment, veterinary and public health laboratories, constructed a dataset of 1484 genomes originating from Lm strains collected in 19 European countries. This dataset encompasses a large number of CCs occurring worldwide, covers many diverse habitats and is balanced between ecological compartments and geographic regions. The dataset presented here will contribute to improve our understanding of Lm ecology and should aid in the surveillance of Lm. This dataset provides a basis for the discovery of the genetic traits underlying Lm adaptation to different ecological niches.
Published: 2022
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34. An Innovative Solid-State Micro-Anaerobic Digestion Process to Valorize Food Waste: Technical Development Constraints and Consequences on Biological Performances

Author: Anne Tremier, Patrick Dabert, Axelle Degueurce, Laurent Blondel, Pascal Peu, Megane Lebreton, S. Picard, Anne Le Bihan, Victor Argence, Martine Sarrazin, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), and Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: Environmental Engineering, Semi-continuous, Methanogenic pathways, Methanogenesis, 020209 energy, Solid-state, Two-stage, 02 engineering and technology, 7. Clean energy, Methane, 12. Responsible consumption, 03 medical and health sciences, chemistry.chemical_compound, Waste production, 11. Sustainability, 0202 electrical engineering, electronic engineering, information engineering, Leachate, Waste Management and Disposal, 0303 health sciences, Trace elements, Waste management, 030306 microbiology, Renewable Energy, Sustainability and the Environment, [SDE.IE]Environmental Sciences/Environmental Engineering, 6. Clean water, Anaerobic digestion, Food waste, chemistry, Scientific method, NGS, Environmental science, Leachate recirculation
Abstract: To face the increase of waste production and meet the energy demand of urban areas, municipal waste management systems should be rethought. Innovative solutions such as decentralised small-scale anaerobic digestion could be developed. This work presents the design, operation and performances of a new micro-scale anaerobic digester (AD) developed to degrade food waste (FW) in urban areas i.e. highly compact and with low water and energy demand. To meet these objectives, the new micro-scale AD is a semi-continuous and two-stage process built vertically to take advantage of the gravity to mix and move the digested matter instead of using mechanical devices. The first stage consists in a tubular reactor fed weekly with FW and periodically watered with leachate from the second stage reactor located below the tubular reactor. Results show that AD performances were highly correlated to the efficiency of hydric transfer between the tubular reactor and the leachate tank. Indeed, pH, volatile fatty acids and microbial community analysis showed that the hydrolysis occurred in the tubular reactor, while the methanogenesis step occurred in the leachate tank. Overall, the average methane production was 143 ± 87 NL/kgvs with an average methane content of 44 ± 10% and the operation mode of the process has still to be improved. Graphic Abstract
Published: 2022
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35. Cellular concrete waste: An efficient new way for H2S removal

Author: Poser, Morgane, Duarte E Silva, Luis Rodolfo, Peu, Pascal, Couvert, Annabelle, Dumont, Éric, Institut des Sciences Chimiques de Rennes (ISCR), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Ecole Nationale Supérieure de Chimie de Rennes (ENSCR)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Agence de l'Environnement et de la Maîtrise de l'Energie (ADEME), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire de génie des procédés - environnement - agroalimentaire (GEPEA), École nationale vétérinaire, agroalimentaire et de l'alimentation Nantes-Atlantique (ONIRIS)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Nantes université - UFR des Sciences et des Techniques (Nantes univ - UFR ST), Nantes Université - pôle Sciences et technologie, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - pôle Sciences et technologie, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - Institut Universitaire de Technologie Saint-Nazaire (Nantes Univ - IUT Saint-Nazaire), Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ), and The authors would like to thank ADEME (N° TEZ19-041) and the Region of Brittany (N°1169) for their financial support.
Subjects: Hydrogen sulfide, [SDE.IE]Environmental Sciences/Environmental Engineering, Calcium oxide, [SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering, Filtration and Separation, Desulfurization, Cellular Concrete Waste, Separation, Analytical Chemistry
Abstract: International audience; The ability of cellular concrete waste (CC) to remove hydrogen sulfide (H2S) from a mimic biogas composed of nitrogen, oxygen and H2S was investigated using abiotic filtration systems for H2S concentration up to 1500 mg m−3 and Empty Bed Residence Time (EBRT) ranging from 30 to 180 s. The influence of the humidity of the material in H2S removal was studied. In wetted conditions (relative humidity > 97 %), 169 g of H2S were removed per kg of material. This value is probably lower than the maximum capacity of the cellular concrete since the experiment was ended before the end-of-life of the material. The H2S elimination capacity of cellular concrete waste could reach up to 32 g m-3 h−1. These performances are due to complex physico-chemical mechanisms operating simultaneously between H2S and the different components of cellular concrete (mainly calcium oxide CaO from the calcium silicate hydrate CaO SiO2 nH2O, and ferric oxide Fe2O3) leading to a modification of the mechanical structure of the material to calcium sulfate (gypsum CaSO4 2H2O) and the production of elemental sulfur (octasulfur S8). Empirical relationships based on H2S concentration and EBRT were established (i) to predict the Removal Efficiency (RE) of the filtration system (logistic equation); (ii) to assess the operating time of the material. Results obtained suggest that this simple, robust and cheap H2S removal technology would be a suitable and valuable technique to treat gas flowrates generated by decentralized domestic biogas digesters.
Published: 2023
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36. Plants as a realized niche for Listeria monocytogenes

Author: Hoai‐Nam Truong, Dominique Garmyn, Laurent Gal, Carine Fournier, Yann Sevellec, Sylvain Jeandroz, Pascal Piveteau, Agroécologie [Dijon], Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), and Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: foodborne pathogen, plant–microbe interaction, Reviews, habitat, Review, microbe‐associated molecular pattern, Microbiology, Disease Outbreaks, Foodborne Diseases, 03 medical and health sciences, Vegetables, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Humans, Listeriosis, Plant Immunity, plant-microbe interaction, 030304 developmental biology, 2. Zero hunger, 0303 health sciences, Microbial Viability, Host Microbial Interactions, 030306 microbiology, Microbiota, fungi, microbe-associated molecular pattern, food and beverages, Plants, 15. Life on land, Listeria monocytogenes, QR1-502, Food Microbiology, Microbial Interactions
Abstract: Listeria monocytogenes is a human pathogen. It is the causative agent of listeriosis, the leading cause of bacterial‐linked foodborne mortality in Europe and elsewhere. Outbreaks of listeriosis have been associated with the consumption of fresh produce including vegetables and fruits. In this review we summarize current data providing direct or indirect evidence that plants can serve as habitat for L. monocytogenes, enabling this human pathogen to survive and grow. The current knowledge of the mechanisms involved in the interaction of this bacterium with plants is addressed, and whether this foodborne pathogen elicits an immune response in plants is discussed., In this review, we summarize current data providing direct or indirect evidence that plants can serve as habitats for Listeria monocytogenes, the causative agent of the food‐borne life‐threatening disease listeriosis. The mechanisms involved in the complex interplay between plants and this bacterium are addressed, and whether this pathogen elicits an immune response in plants is discussed. The combination of plant intrinsic factors, extrinsic biotic factors, and abiotic environmental factors draws the boundaries of plant habitat colonization by L. monocytogenes.
Published: 2021
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37. Real-time algorithm to estimate and predict unsteady flows from few measurements using reduced-order models

Author: Resseguier, Valentin, Ladvig, Matheus, HEITZ, Dominique, L@b SCALIAN, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), and Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: Physics::Fluid Dynamics, Fluid dynamics, uncertainty quantification, [NLIN.NLIN-CD]Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD], stochastic closure, reduced order model, particle filtering, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [SPI.MECA.MEFL]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph]
Abstract: To successfully monitor and actively control hydrodynamic and aerodynamic systems (e.g., wind turbine blade, wind farm, hydrofoil, aircraft wings), it can be critical to estimate and predict the unsteady flow around them in real-time. We propose to introduce a new algorithm to couple onboard measurements with fluid dynamics simulations and data in real-time without the need to rely on an extensive computational infrastructure. This coupling is achieved by combining a Proper Orthogonal Decomposition Galerkin method, a model under location uncertainty stochastic closure, and a particle filtering scheme. We focus our numerical tests on a two-and a three-dimensional wake flows at low and moderate Reynolds numbers, respectively. Using a single measurement point, we obtain almost optimal flow estimations for up to 14 vortex shedding cycles after the learning time window.
Published: 2021

38. MRI investigation of internal defects in potato tubers with particular attention to rust spots induced by water stress

Author: Jérémy Pépin, Carole Deleu, Maja Musse, Gisèle Joly, Sylvain Challois, Laurent Leport, Ghina Hajjar, Stéphane Quellec, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Germicopa, Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), European Regional Development Fund, Université de Rennes (UR)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-INSTITUT AGRO Agrocampus Ouest, and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)
Subjects: 0106 biological sciences, Water stress, Horticulture, Biology, 01 natural sciences, Rust, Transverse NMR relaxation, Magnetic resonance imaging, Water uptake, Internal browning disorder, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Water intake, 2. Zero hunger, Tuber, Spots, [PHYS.PHYS]Physics [physics]/Physics [physics], fungi, food and beverages, 04 agricultural and veterinary sciences, Fast spin echo, Transverse relaxation, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Rust spots, Agronomy and Crop Science, 010606 plant biology & botany, Food Science
Abstract: International audience; Potato quality is a major concern for both producers and customers. However, potato tubers are affected by various forms of internal damage with no external symptoms, leading to substantial economic losses. MRI was used as a non-invasive and quantitative method to evaluate internal defects in potato tubers and their evolution during storage. Rust spots, induced by water stress, were considered in particular. To this end, potato plants were cultivated both in the field and in pots and their water uptake was controlled. Following harvest and throughout the storage period, 3D images of tubers were recorded on a 1.5 T MRI scanner using a fast spin echo sequence. In parallel, the multi-exponential transverse relaxation times (T2) of the tubers were mapped in order to provide information on changes in water status and distribution at the subcellular level in rust spots and in healthy perimedullary regions. The occurrence of rust spots correlated with water conditions in greenhouse where water intake was carefully controlled. The number and individual volume of rust spots did not change during storage period, but they significantly increased with tuber size. Bi-exponential transverse relaxation revealed differences between healthy and damaged tissue.
Published: 2021
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39. Modelling hydrolysis: Simultaneous versus sequential biodegradation of the hydrolysable fractions

Author: Julie Jimenez, Damien J. Batstone, Ángel Robles, Aurora Seco, Fabrice Béline, Cyrille Charnier, Peter A. Vanrolleghem, Mathieu Spérandio, Eberhard Morgenroth, Eric Latrille, Jérôme Harmand, Dominique Patureau, George Ekama, Mokhles Kouas, Jean-Philippe Steyer, Michel Torrijos, Laboratoire de Biotechnologie de l'Environnement [Narbonne] (LBE), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), BioEnTech, Symbiose : Ecosystèmes microbiens et bioprocédés d’épuration et de valorisation (TBI-SYMBIOSE), Toulouse Biotechnology Institute (TBI), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), University of Cape Town, Université Laval [Québec] (ULaval), Universitat Politècnica de València (UPV), Universitat de València (UV), University of Queensland [Brisbane], Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut National de la Recherche Agronomique (INRA), EAWAG SWISS FEDERAL INSTITUTE OF AQUATIC SCIENCE AND TECHNOLOGY DUBENDORF SWE, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), ETH ZURICH INSTITUTE OF ENVIRONMENTAL ENGINEERING ZURICH SWE, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), UNIVERSITY OF CAPE TOWN ZAF, DEPARTAMENT D'ENGINYERIA QUIMICA UNIVERSITAT DE VALENCIA BURJASSOT VALENCIA ESP, and ADVANCED WATER MANAGEMENT CENTRE THE UNIVERSITY OF QUEENSLAND AUS
Subjects: [SDV.BIO]Life Sciences [q-bio]/Biotechnology, Biosolids, SEQUENTIAL EXTRACTION, ANAEROBIC DIGESTION, BIODEGRADATION, 02 engineering and technology, 010501 environmental sciences, TRITICUM AESTIVUM, 01 natural sciences, 7. Clean energy, NUMERICAL MODEL, SLUDGE DIGESTION, Bioreactors, METHANE, BIOLOGICAL MATERIALS, ACTIVATED SLUDGE, 0202 electrical engineering, electronic engineering, information engineering, Anaerobiosis, Sequential model, PRIORITY JOURNAL, Waste Management and Disposal, ComputingMilieux_MISCELLANEOUS, CALIBRATION, Sewage, CONCENTRATION (PARAMETER), Chemistry, FRACTIONATION, ACID HYDROLYSIS, INCUBATION TIME, MODELLING, HYDROLYSIS, CHEMICAL FRACTIONATION, SEQUENTIAL DEGRADATION, Biodegradation, Environmental, WASTE TREATMENT, ORGANIC MATTER, [SDE]Environmental Sciences, ANAEROBIC DIGESTION MODEL, ADM1, SOLID WASTE, 020209 energy, MODELS, Fractionation, CAPACITY, Hydrolysis, DIGESTION, ISOTOPIC FRACTIONATION, NONHUMAN, CHEMICAL OXYGEN DEMAND, ARTICLE, MODEL SELECTION, 0105 earth and related environmental sciences, Chromatography, Models, Theoretical, SUBSTRATES, Biodegradation, SIMULTANEOUS DEGRADATION, HOMOGENEOUS MATERIALS, Anaerobic digestion, WASTE WATER MANAGEMENT, Activated sludge, APPLE, Degradation (geology)
Abstract: Hydrolysis is considered the limiting step during solid waste anaerobic digestion (including co-digestion of sludge and biosolids). Mechanisms of hydrolysis are mechanistically not well understood with detrimental impact on model predictive capability. The common approach to multiple substrates is to consider simultaneous degradation of the substrates. This may not have the capacity to separate the different kinetics. Sequential degradation of substrates is theoretically supported by microbial capacity and the composite nature of substrates (bioaccessibility concept). However, this has not been experimentally assessed. Sequential chemical fractionation has been successfully used to define inputs for an anaerobic digestion model. In this paper, sequential extractions of organic substrates were evaluated in order to compare both models. By removing each fraction (from the most accessible to the least accessible fraction) from three different substrates, anaerobic incubation tests showed that for physically structured substrates, such as activated sludge and wheat straw, sequential approach could better describe experimental results, while this was less important for homogeneous materials such as pulped fruit. Following this, anaerobic incubation tests were performed on five substrates. Cumulative methane production was modelled by the simultaneous and sequential approaches. Results showed that the sequential model could fit the experimental data for all the substrates whereas simultaneous model did not work for some substrates. © 2019
Published: 2020
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40. Enhanced aeration of part-baked bread using a novel combination of baking and partial vacuum

Author: David Grenier, Tiphaine Lucas, D. Le Ray, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), and Université Bretagne Loire (UBL)
Subjects: WATER LOSS, 0106 biological sciences, Thesaurus (information retrieval), OVEN-RISE, STRUCTURE, Materials science, business.industry, 04 agricultural and veterinary sciences, GAS CELL, 040401 food science, 01 natural sciences, 0404 agricultural biotechnology, 010608 biotechnology, [SDE]Environmental Sciences, DENSIFICATION, Aeration, COLLAPSE, Process engineering, business, Food Science
Abstract: International audience; An experimental approach to partial baking of dough rolls at low temperature (< 105°C) and partial vacuum (-20 kPa) was developed. The impact of various partial vacuum and heat transfers at the bottom of dough rolls during baking, on the oven-rise and the crumb structure of baked rolls was evaluated. Oven-rise and crumb structure obtained using partial vacuum were compared to those obtained using a commercial convection oven. A specially Magnetic Resonance Imager (MRI) designed oven was adapted with a temperature-controlled plate to modify the setting of the dough at the bottom of the roll. Dynamic and non-invasive assessment of the structure on the scale of the millimetre was carried out using Magnetic Resonance Imaging. The analysis of the mechanisms involved in the structure setting, on the local scale, was presented according to three stages identified in the oven-rise. No large gas cells and collapse were encountered at the initial lowering in pressure. Partial vacuum produced lower crumb density than that obtained at the atmospheric pressure. The setting of the periphery was involved in the partial collapse at the bottom at the later stage of baking and large rate-of-deformations were involved in the formation of large gas cells.
Published: 2019
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41. Biological Nitrogen Potential (BNP): A New Methodology to Estimate Nitrogen Transformations During Anaerobic Digestion of Organic Substrates

Author: Anne Tremier, Cyril Marcilhac, Younes Bareha, R. Girault, Fabrice Béline, Henry Fisgativa, Caroline Jaudoin, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Université Bretagne Loire (UBL)
Subjects: 0106 biological sciences, Environmental Engineering, 020209 energy, ANAEROBIC DIGESTION, MINERALISATION, Biomass, chemistry.chemical_element, 02 engineering and technology, 01 natural sciences, chemistry.chemical_compound, NITROGEN TRANSFORMATIONS, 010608 biotechnology, 11. Sustainability, 0202 electrical engineering, electronic engineering, information engineering, Ammonium, Waste Management and Disposal, KINETICS, MINERALOGY, Renewable Energy, Sustainability and the Environment, ORGANIC FERTILISATION, PROTEIN HYDROLYSIS, NITROGEN MINERALISATION, MINERALISATION POTENTIAL, SUBSTRATES, Straw, DIGESTATE, INOCULUM TO SUBSTRATE RATIOS, Manure, Nitrogen, 6. Clean water, NITROGEN, Green waste, FERTILISATION, Anaerobic digestion, chemistry, Environmental chemistry, FERTILIZERS, [SDE]Environmental Sciences, Digestate, ENZYME KINETICS, IMMOBILISATION, NITROGEN IMMOBILISATION
Abstract: International audience; In this paper, nitrogen transformations were studied on 13 substrates from agro-industrial, agricultural or urban sources using a new method. This method was developed to determine the kinetics and balance of nitrogen transformation during anaerobic digestion with high inoculum-to-substrate ratio while avoiding instabilities with nutrients addition. Inoculum was washed to reduce ammonium content and carbonates were added to adjust buffer capacity. Results show that kinetics of nitrogen mineralisation depends mainly on initial substrate. Nitrogen was quickly transformed before stabilisation (from 2 to 8 days). Four types of nitrogen transformation were identified: (a) rapid mineralisation (transformation of organic nitrogen (Norg) into ammonium) for blood, (b) moderate mineralisation, for sludge, green waste and food waste, (c) limited protein hydrolysis (no transformation of nitrogen forms) for slurry and manure and, (d) immobilisation of nitrogen (transformation of ammonium into Norg (biomass growth)) for fruits, straw and greases. Biological nitrogen potential (BNP) ranged from ' 7.1 to 22.8 gN kgWW'1 and showed a good correlation (R2 = 0.80) with Norg from substrates. On co-digestion tests, no significant inhibitions of mineralisation nor synergies between substrates were assessed allowing to calculate BNP value of the mix as the weighting average of the BNP values of each added substrate. Examples of calculation of nitrogen form on digestate show that do not use BNP may induce to under or overestimations of the final NH4 + content. A comparison of this methodology with an already published methodology shows an excellent correlation but a systematic difference of 7.2 gN kgWW'1, which seems to be explained by a better capacity of the methodology developed in this study to describe immobilisation phenomena. © 2019, Springer Nature B.V.
Published: 2019
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42. Real-time unsteady air flow prediction to reduces mechanic load variations and wind turbine maintenance costs

Author: Resseguier, Valentin, Ladvig, Matheus, Picard, Agustin Martin, Mémin, Etienne, Heitz, Dominique, Voisin, Dimitry, Braud, Caroline, L@b SCALIAN, Fluid Flow Analysis, Description and Control from Image Sequences (FLUMINANCE), Institut de Recherche Mathématique de Rennes (IRMAR), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-INSTITUT AGRO Agrocampus Ouest, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire de recherche en Hydrodynamique, Énergétique et Environnement Atmosphérique (LHEEA), École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS), ANR-11-LABX-0020,LEBESGUE,Centre de Mathématiques Henri Lebesgue : fondements, interactions, applications et Formation(2011), AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-AGROCAMPUS OUEST, and Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Inria Rennes – Bretagne Atlantique
Subjects: [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [SPI.MECA.MEFL]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph]
Abstract: International audience; For actively controlling aerodynamic systems – like Wind Turbine (WT) blades -- it can be necessary to estimate in real-time and predict the air flow around those systems. We propose here a new method which combines machine learning,physical models and measurements for this purpose. Very good numerical results have been obtained on wake flows.
Published: 2021

43. Towards wind machines park management automatization to improve fight against spring frost events

Author: Le Cap, Clara, Heitz, Dominique, Carlier, Johan, Quenol, Hervé, Buisson, Emmanuel, Weather Measures, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Littoral, Environnement, Télédétection, Géomatique (LETG - Rennes), Littoral, Environnement, Télédétection, Géomatique UMR 6554 (LETG), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Université d'Angers (UA)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Brest (UBO)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Géographie et d'Aménagement Régional de l'Université de Nantes (IGARUN), Université de Nantes (UN)-Université de Nantes (UN)-Université de Caen Normandie (UNICAEN), Université de Nantes (UN)-Université de Nantes (UN), and Heitz, Dominique
Subjects: [SPI.MECA.MEFL] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph], [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, ComputingMilieux_MISCELLANEOUS, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, [SPI.MECA.MEFL]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph]
Abstract: International audience
Published: 2021

44. Circular Economy Applied to Organic Residues and Wastewater: Research Challenges

Author: Nicolas Bernet, Patrick Dabert, Jean-Marc Choubert, Eric Trably, Jacques Mery, Diana Garcia-Bernet, Christian Duquennoi, Sylvie Gillot, Anne Tremier, Bénédicte Bakan, Rachel Boutrou, Théodore Bouchez, Jean-Philippe Steyer, Caroline Rémond, Vincenza Ferraro, Unité de recherche sur les Biopolymères, Interactions Assemblages (BIA), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire de Biotechnologie de l'Environnement [Narbonne] (LBE), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Procédés biotechnologiques au service de l'environnement (UR PROSE), Science et Technologie du Lait et de l'Oeuf (STLO), AGROCAMPUS OUEST, Réduire, valoriser, réutiliser les ressources des eaux résiduaires (UR REVERSAAL), Qualité des Produits Animaux (QuaPA), Fractionnement des AgroRessources et Environnement (FARE), Université de Reims Champagne-Ardenne (URCA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE)
Subjects: Value (ethics), Environmental Engineering, 020209 energy, 02 engineering and technology, 010501 environmental sciences, Wastewater, 01 natural sciences, 12. Responsible consumption, [SPI]Engineering Sciences [physics], Resource (project management), 11. Sustainability, Evaluation methods, 0202 electrical engineering, electronic engineering, information engineering, Circular Economy, Waste Management and Disposal, 0105 earth and related environmental sciences, 2. Zero hunger, [SDV.EE]Life Sciences [q-bio]/Ecology, environment, Renewable Energy, Sustainability and the Environment, business.industry, [SDE.IE]Environmental Sciences/Environmental Engineering, Circular economy, 15. Life on land, Environmental economics, Research Challenge, 6. Clean water, 13. Climate action, Agriculture, Paradigm shift, 8. Economic growth, Urban system, Business, Organic Residue
Abstract: To move today’s agricultural and urban systems towards tomorrow’s circular economy and respond to climate change, it is imperative to turn organic residues and wastewater into resourceful assets. This article discusses the changes that are needed in research to drive this paradigm shift and to go from a “losses and waste” situation to a “resource and opportunities” ambition. The current lines of research aim to maximise the use and value of biomass or organic residues and wastewater and propose new organisational schemes driven by technical innovations. Exploring the pathways to a sustainable future through many domains let us identify five challenges to structure the research efforts and find circular bioeconomy solutions for organic residues and wastewater: (1) proposing innovative processes and integrated multi-process systems; (2) promoting the emergence of multi-scale and cross-sectoral organisations; (3) developing multi-performance evaluation methods, (4) rethinking research–society intersections, and (5) enhancing research–legislation interactions. We end by outlining prospects for moving forward past current limitations: beyond increasing knowledge, research will continue its own transition. Our responsibility today is not to think about what we could do for a better world but what we should do to make our ever-changing world even better and more sustainable. Graphic Abstract
Published: 2021
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45. MRI Relaxometry in Food Science

Author: Musse, Maja, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Musse, Maja
Subjects: [PHYS]Physics [physics], ComputingMilieux_MISCELLANEOUS, [PHYS] Physics [physics]
Abstract: International audience
Published: 2021

46. MRI Study of Temperature Dependence of Multi-exponential Transverse Relaxation Times in Tomato

Author: François Mariette, Rodolphe Leforestier, Maja Musse, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), and Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: 0106 biological sciences, 0303 health sciences, Materials science, Aqueous solution, Solid-state physics, [PHYS.PHYS]Physics [physics]/Physics [physics], food and beverages, 01 natural sciences, Atomic and Molecular Physics, and Optics, Exponential function, 03 medical and health sciences, Magnetization, Membrane, Transverse relaxation, Chemical physics, Molecule, Dispersion (chemistry), 030304 developmental biology, 010606 plant biology & botany
Abstract: International audience; The effects of the temperature on the multi-exponential transverse relaxation signal of fruit tissues were studied by MRI at 1.5 T, with tomato as an example of fleshy fruits. The relative importance of chemical exchange mechanisms was investigated by comparing the results obtained from tomatoes with those obtained from aqueous solutions made up to simulate the vacuolar water pool. A more extended analysis of the effects of chemical exchanges on transverse relaxation time distributions was performed using the two-site Carver and Richards’s expression, by fitting the experimental dispersion curves with the theoretical model. At temperatures between 7 and 32 °C, the transverse relaxation signal in tomato pericarp was multi-exponential, indicating that cell membranes acted, at least partially, as barriers to diffusive exchanges of water molecules between cell compartments. Unexpectedly, the transition from two to three peaks in the T2 distribution occurred between 7 and 15 °C for most of the tomatoes analyzed. Further, the relaxation time of the vacuolar water pool of the tomato pericarp remained mostly stable with temperature, which was contrary to expectations when only chemical exchange mechanisms were taken into account. It was deduced that additional mechanisms compensated for the expected increase in T2 in the tomato pericarp. The hypotheses were discussed, in which the loss of the water magnetization at the membranes was assumed to be produced either by diffusive exchanges between compartments or by chemical exchanges between protons from water molecules and solid membranes.
Published: 2021
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47. Particle position prediction based on Lagrangian coherency for flow over a cylinder in 4D-PTV

Author: Ali Rahimi Khojasteh, Dominique Heitz, Yin Yang, Lionel Fiabane, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), and Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: Physics::Fluid Dynamics, Lagrangian coherent structure, Lagrangian particle tracking, Particle tracking techniques, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [SPI.MECA.MEFL]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph]
Abstract: International audience; Recent developments in time-resolved Particle Tracking Velocimetry (4D-PTV) consistently improved tracking accuracy and robustness. We propose a novel technique named "Lagrangian coherent predictor" to estimate particle positions within the 4D-PTV algorithm. We add spatial and temporal coherency information of neighbour particles to predict a single trajectory using Lagrangian Coherent Structures (LCS). We found that even a weak signal from coherent neighbour motions improves particle prediction accuracy in complex flow regions. We applied Finite Time Lyapunov Exponent (FTLE) to quantify local boundaries (i.e. ridges) of coherent motions. Synthetic analysis of the wake behind a smooth cylinder at Reynolds number equal to 3900 showed enhanced estimation compared with the recent predictor functions employed in 4D-PTV. Results of the experimental study of the same flow configuration are reported. We compared predicted positions with the optimised final positions of Shake The Box (STB). It was found that the Lagrangian coherent predictor succeeded in estimating particle positions with minimum deviation to the optimised positions.
Published: 2021

48. Adjustable interrogation window for 2D PIV estimation based on local Lagrangian coherency

Author: Ali Rahimi Khojasteh, Dominique Heitz, Yin Yang, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), and Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: Physics::Fluid Dynamics, Lagrangian coherent structure, Optical flow OF, PIV - Particle Image Velocimetry, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [SPI.MECA.MEFL]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph]
Abstract: International audience; We present a novel approach to adjust shapes of the interrogation windows (IW) in Particle Image Velocimetry (PIV) measurements as a function of temporal and spatial local coherent motions. Lagrangian Coherent Structures (LCS) has been widely utilized to determine local flow boundaries. We propose using Finite-Time Lyapunov Exponent (FTLE) to quantify LCS separatrix boundaries (i.e. ridges) and adjust the interrogation window. We integrated the proposed method with a local optical flow PIV algorithm. The evaluation was performed using synthetic particle images of 2D homogeneous isotropic turbulence obtained from Direct Numerical Simulation (DNS). The results showed significant improvements in regions with complex flow behaviours, particularly shear, vortex and hyperbolic motions. We studied improvements of the velocity estimation in a real experiment of the wake flow behind a cylinder at Reynolds number equal to 3900. It was found that optical flow featured by coherency based interrogation window (coherent optical flow) reveals detailed vector field estimations in regions with complex behaviours inside the wake flow.
Published: 2021

49. Joint study of spatial variability of temperatures and wind machine performance in the Quincy vineyard to improve fight against spring frost events

Author: Clara Le Cap, Johan Carlier, Hervé Quénol, Dominique Heitz, Emmanuel Buisson, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Weather Measures, Littoral, Environnement, Télédétection, Géomatique (LETG - Rennes), Littoral, Environnement, Télédétection, Géomatique UMR 6554 (LETG), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Université d'Angers (UA)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Brest (UBO)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Géographie et d'Aménagement Régional de l'Université de Nantes (IGARUN), Université de Nantes (UN)-Université de Nantes (UN)-Université de Caen Normandie (UNICAEN), Université de Nantes (UN)-Université de Nantes (UN), and Heitz, Dominique
Subjects: gel, spring frosts, vignoble de Quincy, vineyard of Quincy, gelées printanières frost, [SPI.MECA.MEFL] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph], [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation, wind machine, tour antigel, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, [SPI.MECA.MEFL]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph]
Abstract: Spring frosts occurring after budburst constitute a significant risk for winegrowers and can lead to severe yield losses. Wind machines can contribute to protecting vineyards against these frost events. However, the efficiency of wind machine parks depends on the locations of wind machines concerning their performance and spatial variability of temperature during these frost events. This study aims to characterize wind machine performance and spatial variability of temperature, and propose a methodology for an a priori positioning wind machines on the vineyard of Quincy. To face this stake, the CUMA of Quincy vineyard came up with several partners in the SICTAG project (“Innovant System of Connected decision support and efficient real-time management of wind machine of the Centre Val de Loire”)., Les gelées printanières survenant après le débourrement des bourgeons sont particulièrement dévastatrices et conduisent pour les vignerons à une perte économique importante. Les tours antigel sont un des moyens existants permettant de lutter contre ces gelées. Cependant, l'efficacité d'un parc de tours dépend de leur positionnement, déterminé par les performances de la tour et de la variabilité spatiale de la température durant ces évènements gélifs. L'objectif de cette étude est de caractériser les performances des tours antigel et la variabilité de la température, permettant ainsi de proposer une méthodologie pour un positionnement a priori des tours antigel dans le vignoble de Quincy.
Published: 2021

50. Eco-friendly feed formulation and associated environmental impacts of pig production

Author: De Quelen, Francine, Labussière, Etienne, Wilfart, Aurélie, Garcia-Launay, Florence, Guiziou, Fabrice, Nunes, Guillaume, Béline, Fabrice, Dourmad, Jean-Yves, Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Sol Agro et hydrosystème Spatialisation (SAS), Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Bernard, Emilie
Subjects: Feed ingredients, Manure management, Pig systems, [SDV.SA.SPA]Life Sciences [q-bio]/Agricultural sciences/Animal production studies, [SDV.SA.SPA] Life Sciences [q-bio]/Agricultural sciences/Animal production studies, Environmental impacts, Respiratory chambers, ComputingMilieux_MISCELLANEOUS, LCA life cycle assessment
Abstract: International audience
Published: 2021

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