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A hydrodynamic model coupled with a particle tracking model was used to identify the pathways and accumulation areas of microplastics (MP) in the Gulf of Finland (GoF) over a three-year period (2018-2020). Two key sources, wastewater treatment plants (WWTPs) and rivers, were considered, focusing on polypropylene (PP)/polyethylene (PE) and polyethylene terephthalate (PET) particles sized 20-500 μm. Rivers contribute 76% of total MP entering the gulf, while WWTPs account for the remaining 24%. Most of the MP accumulates inside the gulf and does not drift to the Baltic Proper. The eastern part of the gulf exhibits the highest surface concentrations of particles influenced by the Neva River. In the water column, MP concentrations were notably high in shallow coastal areas, decreasing gradually offshore. Potential MP accumulation zones were identified primarily between longitudes 28°E and 30°E, particularly near the major rivers Narva and Kymi and in the easternmost gulf related to the Neva River discharge. The MP concentrations in the surface layer and water column were higher in winter while settling was more intense in summer. Short-term variability in the surface layer was caused by (sub)mesoscale advection and divergence/convergence, while in the near-bottom layer, strong bottom currents and consequent resuspension elevated the concentrations. [ABSTRACT FROM AUTHOR]

A hydrodynamic model coupled with a particle tracking model was used to identify the pathways and accumulation areas of microplastics (MP) in the Gulf of Finland (GoF) over a three-year period (2018-2020). Two key sources, wastewater treatment plants (WWTPs) and rivers, were considered, focusing on polypropylene (PP)/polyethylene (PE) and polyethylene terephthalate (PET) particles sized 20-500 μm. Rivers contribute 76% of total MP entering the gulf, while WWTPs account for the remaining 24%. Most of the MP accumulates inside the gulf and does not drift to the Baltic Proper. The eastern part of the gulf exhibits the highest surface concentrations of particles influenced by the Neva River. In the water column, MP concentrations were notably high in shallow coastal areas, decreasing gradually offshore. Potential MP accumulation zones were identified primarily between longitudes 28°E and 30°E, particularly near the major rivers Narva and Kymi and in the easternmost gulf related to the Neva River discharge. The MP concentrations in the surface layer and water column were higher in winter while settling was more intense in summer. Short-term variability in the surface layer was caused by (sub)mesoscale advection and divergence/convergence, while in the near-bottom layer, strong bottom currents and consequent resuspension elevated the concentrations.

Benthic storms are episodes of intensified near‐bottom currents capable of sediment resuspension in the deep ocean. They typically occur under regions of high surface eddy kinetic energy (EKE), such as the Gulf Stream. Although they have long been observed, the mechanism(s) responsible for their formation and their relationships with salient features of the deep ocean, such as bottom mixed layers (BMLs) and benthic nepheloid layers (BNLs), remain poorly understood. Here we conduct idealized experiments with a primitive‐equation model to explore the impacts of the unforced instability of a surface‐intensified jet on near‐bottom flows of a deep zonal channel. Vertical resolution is increased near the bottom to represent the bottom boundary layer. We find that the unstable near‐surface jet develops meanders and evolves into alternating, deep‐reaching cyclones and anticyclones. Simultaneously, EKE increases near the bottom due to the convergence of vertical eddy pressure fluxes, leading to near‐bottom currents comparable to those observed during benthic storms. These currents in turn form BMLs with thickness of O(100 m) from enhanced velocity shears and turbulence production near the bottom. The deep cyclonic eddies transport fluid particles both laterally and vertically, from near the bottom through the entire BML and may contribute to the formation of the lower part of BNLs. A sloping bottom reduces both the intensity of the near‐bottom currents and the extent of vertical transport. Overall, our study highlights a significant response of the abyssal environment to near‐surface current instability, with potential implications for sediment transport in the deep ocean. Plain Language Summary: Benthic storms are episodes of vigorous near‐bottom currents that are capable of sediment resuspension at abyssal depths in the ocean. They typically occur in regions characterized by strong and unstable currents near the surface, such as the Gulf Stream. In this study, we use an ocean circulation model to simulate the instability of a surface current like the Gulf Stream, and to explore the effects of this instability on the environment near the bottom in an idealized oceanic basin. We find that strong cyclonic and anticyclonic currents are simulated near the bottom in response to the instability of the surface current. The intensity of deep currents varies strongly with distance from the bottom, which creates turbulence and a well‐mixed layer adjacent to the deep seabed. In deep cyclones, particles from near the bottom can be transported upward through the entire well‐mixed layer. A steeper topographic slope reduces both the intensity of the bottom currents and the vertical displacement of particles. Overall, our study shows that the physical environment near the bottom may exhibit a strong response to the instability of surface currents, which may have a potentially significant impact on the transport of fine sediment from the seafloor. Key Points: Bottom currents simulated from the intrinsic instability of a near‐surface jet reach speeds similar to those observed during benthic stormsAbyssal eddy kinetic energy increases, producing deep eddies, strong local turbulence, and bottom mixed layers up to O(100 m) thickParticles near the bottom are advected both laterally and vertically in deep cyclones, with potential implications for sediment transport [ABSTRACT FROM AUTHOR]

This study presents a method to simulate hydrogen jet fire using the Fire Dynamics Simulator (FDS). To avoid modeling an actual nozzle, high-speed Lagrangian particles released from a virtual nozzle are introduced to simulate released hydrogen. The capability of this FDS model to predict gas temperature is validated by comparing simulation results with five existing experiments in a rectangular steel compartment with an open end. The effects of relevant parameters prescribed in the FDS model on the gas temperature are also analyzed, including numerical parameters (auto-ignition exclusion zone, offset, particle count, and grid) and physical parameters (particle velocity, spray angle, and auto-ignition temperature). The results show that gas temperatures near the nozzle are sensitive to these parameters. Based on the grey relational analysis, the auto-ignition temperature is the least important parameter to predict gas temperatures, while the grid is the most significant parameter for gas temperatures near the ceiling. • High-speed Lagrangian particles are introduced to simulate the released hydrogen in FDS. • Hydrogen jet fire models are validated by 5 fire tests in a steel compartment. • The gas temperature of the hydrogen jet fire is analyzed with different parameters. • The grey relational analysis method is used for evaluating the effects of parameters. [ABSTRACT FROM AUTHOR]

In instrumented prescribed fires, the ignition procedure requires much attention. In this paper, we investigate the effects of two ignition procedures on the fire head using a 3D numerical model. The first procedure is to ignite the fire from the edges of the fire line towards the centre of the line. The second procedure consists of igniting the fire from the centre of the fire line to the edges of the line. The 3D numerical model used is based on the modelling of the fuel layer from Lagrangian particles, and the fire propagation is based on a two-phase model. The model was tested on an experimental fire in a wheat field in southern Australia. The model predicted the experimental fire front well. Analysis of the impact of the ignition procedure on the fire head showed that the quasi-steady-state rate of fire spread was the same for both procedures. However, before the quasi-stationary state, the front of the first procedure spread faster than that of the second procedure. The fire front in the first procedure was wider than in the second procedure. It was also found that the length of the head fire in the first procedure remained the same as that of the ignition line. In the second procedure, the length of the head fire was one-third of that of the ignition line. [ABSTRACT FROM AUTHOR]

A one-layer particle level set method in which Lagrangian particles are employed to track the interface features is proposed and utilized to capture the interface. First, the interface is captured by utilizing the level set method. Then, the interface is corrected based on the position information of Lagrangian particles and the smooth and accurate interface is obtained. The defect of poor volume conservation properties of the level set method is overcome, which greatly improves the accuracy of the moving interface. After that, a simple and effective particle reallocation strategy is presented, including the addition and deletion of particles, so that the method can accurately handle complex topological changes such as the interface merging and separation. Finally, the method proposed is verified by several benchmark examples, which can be used to accurately describe the moving interface.

Firebrands (often called embers) increase the propagation rate of wildfires and often cause the ignition and destruction of houses. Predicting the motion of firebrands and the ignition of new fires is therefore of significant interest to fire authorities. Numerical models have the potential to accurately predict firebrand transport. The present study focuses on conducting a set of benchmark experiments using a novel firebrand generator, a device that produces controlled and repeatable sets of firebrands, and validating a numerical model for firebrand transport against this set of experiments. The validation is conducted for the transport of non-burning and burning cubiform firebrand particles at two flow speeds. Four generic drag sub-models used to estimate drag coefficients that are suited for a wide variety of firebrand shapes are verified for their applicability to firebrand transport modelling. The four sub-models are found to be good in various degrees at predicting the transport of firebrand particles. [ABSTRACT FROM AUTHOR]

In Lagrangian stochastic collision models, a fictitious particle is generated to act as a collision partner, with a velocity correlated to the velocity of the real colliding particle. However, most often, the fluid velocity seen by this fictitious particles is not accounted for in the generation of the fictitious particle velocity, leading to a de-correlation between the fictitious particle velocity and the local fluid velocity, which, after collision, leads to an unrealistic de-correlation of the real particle velocity and the fluid velocity as seen by the particle. This de-correlation, in turn, causes a spurious decrease of the particle kinetic energy, even though the collisions are assumed perfectly elastic. In this paper, we propose a new model in which the generated fictitious particle velocity is correctly correlated to both the real particle velocity and the local fluid velocity at the particle, hence preventing the spurious loss of the total particle kinetic energy. The model is suitable for small inertial particles. Two algorithms for integrating the collision frequency are also compared to each other. The models are validated using large eddy simulation (LES) of mono-dispersed particle-laden stationary homogeneous isotropic turbulence. Simulations are conducted with spherical particles with different turbulent Stokes number, S t t = [ 0.75 - 5.8 ] , and volume fractions, α p = [ 0.014 - 0.044 ] , and are compared to the results of the LES using a deterministic discrete particle simulation model. [ABSTRACT FROM AUTHOR]

In this work, the reconstruction of sub-grid scales in large eddy simulation (LES) of turbulent flows in stratocumulus clouds is addressed. The approach is based on the fractality assumption of turbulent velocity field. The fractal model reconstructs sub-grid velocity field from known filtered values on LES grid, by means of fractal interpolation, proposed by Scotti and Meneveau (Physica D 127, 198–232 1999). The characteristics of the reconstructed signal depend on the stretching parameter d, which is related to the fractal dimension of the signal. In many previous studies, the stretching parameter values were assumed to be constant in space and time. To improve the fractal interpolation approach, we account for the stretching parameter variability. The local stretching parameter is calculated from direct numerical simulation (DNS) data with an algorithm proposed by Mazel and Hayes (IEEE Trans. Signal Process 40(7), 1724–1734, 1992), and its probability density function (PDF) is determined. It is found that the PDFs of d have a universal form when the velocity field is filtered to wave-numbers within the inertial range. In order to investigate Reynolds number (Re) dependence, we compare the inertial-range PDFs of d in DNS and large eddy simulation (LES) of stratocumulus cloud-top and experimental airborne data from Physics of Stratocumulus Top (POST) research campaign. Next, fractal reconstruction of the subgrid velocity is performed and energy spectra and statistics of velocity increments are compared with DNS data. It is assumed that the stretching parameter d is a random variable with the prescribed PDF. We show that the agreement with the DNS is in such case better and the error in mass conservation is smaller compared to the use of constant values of d. The motivation of this study is to reproduce effect of sub-grid scales on a motion of Lagrangian particles (e.g. droplets) in clouds. [ABSTRACT FROM AUTHOR]

In this study, we simulate three-dimensional transport of algal blooms in Lake Erie using a combination of remote sensing and hydrodynamic modelling. The remote sensing algorithms use data from the Sentinel-3 OLCI satellite sensor to derive chlorophyll-a concentration from cyanobacteria blooms in Lake Erie. The derived chlorophyll-a concentration initializes an algal bloom transport model driven by the lake component of the Water Cycle Prediction System for the Great Lakes, a system of coupled atmosphere-lake-hydrological models operated out of Environment and Climate Change Canada. The bloom is modelled as Microcystis aeruginosa , a buoyant species that is often dominant in harmful algal blooms in western Lake Erie. Short-term (a few days) predictions of algal bloom transport from July 27 to October 8, 2017 are modelled in both Eulerian and Lagrangian frameworks. The Eulerian framework is used to evaluate the sensitivity of model results to the initial vertical distribution of the bloom. In this work, the Lagrangian framework is limited to two-dimensional surface confined particles. We use several error metrics to evaluate model predictions. We find that results are sensitive to the buoyancy velocity for cases where the bloom was initially distributed over a large portion of the water column. An initial vertical distribution selected from modelled chlorophyll-a half depth shows the highest accuracy for the entire range of buoyancy velocities tested. We also find that the Pierce skill score is difficult to interpret, particularly in cases where bloom intensity is greatly overpredicted by the model. [ABSTRACT FROM AUTHOR]

Airworthiness standards require a fire resistance demonstration for aircraft or helicopter engines to obtain a type certificate. This demonstration relies on tests performed with prototype engine parts in the late stages of the development. In hardest tests, a kerosene standardized flame with imposed burnt gas temperature and heat flux is placed next to the engine casing during a given time. The aim of this work is to provide a better characterization of a kerosene/air certification burner in order to reach a better understanding of the thermal environment during fire tests. To this purpose, Large-Eddy Simulation (LES) of the certification burner is carried out. Spray combustion, forced convection on walls and conduction in the solid parts of the burner are coupled to achieve a detailed description of heat transfer. In a first place, physical aspects involved inside the burner in an adiabatic case are described. Then, differences that exist with a conjugate convective and conductive heat transfer case are analyzed. To a larger extent, the aim is to have a better characterization of the flow impinging the casing and to progress on fire test modeling so as to minimize the risks of test failure. [ABSTRACT FROM AUTHOR]

Maintaining and enabling evolutionary processes within meta-populations are critical to resistance, resilience and adaptive potential. Knowledge about which populations act as sources or sinks, and the direction of gene flow, can help to focus conservation efforts more effectively and forecast how populations might respond to future anthropogenic and environmental pressures. As a foundation species and habitat provider, Zostera marina (eelgrass) is of critical importance to ecosystem functions including fisheries. Here, we estimate connectivity of Z. marina in the Skagerrak-Kattegat region of the North Sea based on genetic and biophysical modelling. Genetic diversity, population structure and migration were analysed at 23 locations using 20 microsatellite loci and a suite of analytical approaches. Oceanographic connectivity was analysed using Lagrangian dispersal simulations based on contemporary and historical distribution data dating back to the late 19th century. Population clusters, barriers and networks of connectivity were found to be very similar based on either genetic or oceanographic analyses. A single-generation model of dispersal was not realistic, whereas multigeneration models that integrate stepping-stone dispersal and extant and historic distribution data were able to capture and model genetic connectivity patterns well. Passive rafting of flowering shoots along oceanographic currents is the main driver of gene flow at this spatial-temporal scale, and extant genetic connectivity strongly reflects the "ghost of dispersal past" sensu Benzie, 1999. The identification of distinct clusters, connectivity hotspots and areas where connectivity has become limited over the last century is critical information for spatial management, conservation and restoration of eelgrass. [ABSTRACT FROM AUTHOR]

The variance among bin counts is one of the most effective and convenient indices to quantify the degree of spatial distributive mixing. Although it is suitable for evaluating the spatial distribution of unimodal particles, many practical particle-mixing processes involve bimodal or multimodal particle systems. Herein, the variance among bimodal bin counts is introduced as a new mixing index to quantify the degree of distributive mixing of bimodal or multimodal particles. Four bimodal particle-mixing systems are assumed and analyzed to evaluate index performance: balanced versus imbalanced and fully versus partially distributed particle systems. As a result, we suggest practical usage and the most effective variation of variances among conventional bin counts and bimodal bin counts to quantify the four bimodal particle-mixing systems. Furthermore, variations of the method for evaluating multimodal mixing are proposed. [ABSTRACT FROM AUTHOR]

Firebrands are a harbinger of damage to infrastructure; their effects cause a particularly important threat to people living within the wildland-urban-interface. Short-range firebrands travel with the wind with little or no lofting, and cause spotfires. In this work, the design of a novel firebrand generator prototype is discussed to achieve a uniform shower of firebrands. The transport of short-range firebrand is studied to verify the existing Lagrangian particle model of Fire Dynamics Simulator. Uniform, non-combusting cubiform and cylindrical firebrands are projected using the firebrand generator. The experimentally observed distribution of particles on the ground is compared with a simulated distribution using the fire dynamic simulator. The results show that the existing Lagrangian model gives a good agreement with the experimental data. [ABSTRACT FROM AUTHOR]

Multiple tornado events frequently occur in different parts of the world. A region that seems favorable for recurring multiple tornado events due to its geographical location and topography is the eastern sector of the Trans-Mexican Volcanic Belt. A notable multiple tornado event that occurred in this region is investigated. It consisted of five simultaneous tornadoes during the convergence of three air masses: a cold air mass displaced from the north with moderately high relative humidity and specific humidity, a comparatively warm air mass with moderate relative humidity from the southeast, and a hotter air mass with low relative humidity from the southwest. This situation generated a line of intense horizontal wind shear through which the five tornadoes occurred. Numerical simulations revealed three cyclonic vortices and other minor disturbances along the shear line. Vertical cross-sections show rising air in these disturbances suggesting a cyclonic character. The results indicate that the relatively warm mass from the southeast moves over the one associated with a cold front coming from the north, generating multiple cyclonic rotation zones. Experiments with Lagrangian particles revealed vertical movements in the cyclonic rotation zones implying that the maximum heights of the tornadoes varied between 1000 and 1500 m. Moisture flux convergence calculations display structures resembling Kelvin-Helmholtz instabilities. This research proposes a conceptual model where the convergence of masses induced by topography can lead to multiple tornado generation. • Air masses flows in a complex topography led to multiple simultaneous tornadoes. • The topography creates scenarios for the generation of vorticity. • Patterns similar to Kelvin-Helmholtz instabilities appear in the tornadoes area. • The model was able to simulate the spiral cyclonic vertical track. [ABSTRACT FROM AUTHOR]

In this study, a method which allows for causal backtracing of turbulent flow phenomena is suggested. Key events in technical processes based on turbulent mixing can thereby be studied by their detailed temporal and spatial convective history. As a demonstration case for this method, a study of cyclic variations in internal combustion engines is used. Since it is assumed that major influences on cyclic variations are transported convectively, a set of Lagrangian tracer particles is generated at the start of a simulation run. The simulation is performed until the point where an arbitrary phenomenon of interest is observed and the simulation run is cancelled. The method then identifies particles in the neighboring region and saves their identification. Subsequently, the simulation is restarted using the same exact initial flow conditions for artificial turbulence generation and recreates the previous run. However, in the second run, only the identified particles are simulated and their spatial and temporal trajectories are logged and observed in detail. The trajectory provides information on pressure, temperature, velocities and mixture composition to reconstruct the causes of the phenomenon of interest. This approach offers an efficient work-around of computational memory and input/output problems, which occur in modern computational fluid dynamics while also saving temporal and spatial information of small parts in the computational domain. The presented method can be of fundamental value in the research of cyclical processes with complex flows. • A novel temporal backtracing method for the study of flow processes is proposed. • The method studies temporal and spatial dependancies of thermo/fluiddynamical states. • The cyclical variation of an internal combustion engine serves as a test case. • The method focuses on transport phenomena but is also applicable for DNS. [ABSTRACT FROM AUTHOR]

High-Reynolds number homogeneous isotropic turbulence (HIT) is fully described within the Navier-Stokes (NS) equations, which are notoriously difficult to solve numerically. Engineers, interested primarily in describing turbulence at a reduced range of resolved scales, have designed heuristics, known as large eddy simulation (LES). LES is described in terms of the temporally evolving Eulerian velocity field defined over a spatial grid with the mean-spacing correspondent to the resolved scale. This classic Eulerian LES depends on assumptions about effects of subgrid scales on the resolved scales. Here, we take an alternative approach and design LES heuristics stated in terms of Lagrangian particles moving with the flow. Our Lagrangian LES, thus L-LES, is described by equations generalizing the weakly compressible smoothed particle hydrodynamics formulation with extended parametric and functional freedom, which is then resolved via Machine Learning training on Lagrangian data from direct numerical simulations of the NS equations. The L-LES model includes physics-informed parameterization and functional form, by combining physics-based parameters and physics-inspired Neural Networks to describe the evolution of turbulence within the resolved range of scales. The subgrid-scale contributions are modeled separately with physical constraints to account for the effects from unresolved scales. We build the resulting model under the differentiable programming framework to facilitate efficient training. We experiment with loss functions of different types, including physics-informed ones accounting for statistics of Lagrangian particles. We show that our L-LES model is capable of reproducing Eulerian and unique Lagrangian turbulence structures and statistics over a range of turbulent Mach numbers.

This paper presents highly resolved large eddy simulations (LES) of an internal combustion engine (ICE) using an immersed boundary method (IBM), which can describe moving and stationary boundaries in a simple and efficient manner. In this novel approach, the motion of the valves and the piston is modeled by Lagrangian particles, whilst the stationary parts of the engine are described by a computationally efficient IBM. The proposed mesh-free technique of boundary representation is simple for parallelization and suitable for high performance computing (HPC). To demonstrate the method, LES results are presented for the flow and the combustion in an internal combustion engine. The Favre-filtered Navier-Stokes equations are solved for a compressible flow employing a finite volume method on Cartesian grids. Non-reflecting boundary conditions are applied at the intake and the exhaust ports. Combustion is described using a flame surface density (FSD) model with an algebraic reaction rate closure. A simplified engine with a fixed axisymmetric valve (see Appendix A) is employed to show the correctness of the method while avoiding the uncertainties which may be induced by the complex engine geometry. Three test-cases using a real engine geometry are investigated on different grids to evaluate the impact of the cell size and the filter width. The simulation results are compared against the experimental data. A good overall agreement was found between the measurements and the simulation data. The presented method has particular advantages in the efficient generation of the grid, high resolution and low numerical dissipation throughout the domain and an excellent suitability for massively parallel simulations. [ABSTRACT FROM AUTHOR]

This study investigates growth processes of raindrops and the role of recirculation of raindrops for the formation of precipitation in shallow cumulus. Two related cases of fields of lightly precipitating shallow cumulus are simulated using Large-Eddy Simulation combined with a Lagrangian drop model for raindrop growth and a cloud tracking algorithm. Statistics from the Lagrangian drop model yield that most raindrops leave the cloud laterally and then evaporate in the subsaturated cloud environmental air. Only 1%-3% of the raindrops contribute to surface precipitation. Among this subsample of raindrops that contribute to surface precipitation, two growth regimes are identified: those raindrops that are dominated by accretional growth from cloud water, and those raindrops that are dominated by selfcollection among raindrops. The mean cloud properties alone are not decisive for the growth of an individual raindrop but the in-cloud variability is crucial. Recirculation of raindrops is found to be common in shallow cumulus, especially for those raindrops that contribute to surface precipitation. The fraction of surface precipitation that is attributed to recirculating raindrops differs from cloud to cloud but can be larger than 50%. This implies that simple conceptual models of raindrop growth that neglect the effect of recirculation disregard a substantial portion of raindrop growth in shallow cumulus. [ABSTRACT FROM AUTHOR]

Partial differential equations (PDEs) on surfaces arise in a wide range of applications. The closest point method (Ruuth and Merriman (2008) [20] ) is a recent embedding method that has been used to solve a variety of PDEs on smooth surfaces using a closest point representation of the surface and standard Cartesian grid methods in the embedding space. The original closest point method (CPM) was designed for problems posed on static surfaces, however the solution of PDEs on moving surfaces is of considerable interest as well. Here we propose solving PDEs on moving surfaces using a combination of the CPM and a modification of the grid based particle method (Leung and Zhao (2009) [12] ). The grid based particle method (GBPM) represents and tracks surfaces using meshless particles and an Eulerian reference grid. Our modification of the GBPM introduces a reconstruction step into the original method to ensure that all the grid points within a computational tube surrounding the surface are active. We present a number of examples to illustrate the numerical convergence properties of our combined method. Experiments for advection–diffusion equations that are strongly coupled to the velocity of the surface are also presented. [ABSTRACT FROM AUTHOR]

This study investigates the role of topography-induced turbulence, generated by an idealized urban region, in the transport of firebrands and risk of spotting. Flight dispersion, deposition, and smoldering state of tens of thousands of individual mass and size-changing firebrands were investigated in the atmospheric boundary layer turbulence, which was obtained using Large-eddy simulations. Firebrands were assumed to be smoldering spherical particles of Stokes numbers ranging from 30 to 175. indicate that the presence of urban topography significantly affects the firebrand flight behavior, landing distribution, and risk of spotting. Compared to a case with flat topography, horizontal dispersions of the smallest size firebrands were significantly enhanced when urban topography was presented, while the largest firebrands landed closer to each other and closer to the release point. Consequently, a notably different and more compact spotting risk map was achieved. Within the urban boundary layer turbulence, firebrands had a shorter flight and smoldering times in comparison with the flat case. As a result, firebrands landed with larger temperatures, which contributed to a higher risk of spotting in the presence of urban topography. [ABSTRACT FROM AUTHOR]

An investigation of the local flame extinction and re-ignition of hydrogen syngas non-premixed flame are carried out using one-dimensional turbulence (ODT) model with detailed chemistry. Based on the Lagrangian tracer method and chemical explosive mode analysis (CEMA), diagnostic tools have been defined to distinguish the different scenarios of local extinction and re-ignition. The results show that the extinction regime can be characterized by a large negative Damköhler number based on CEMA. From Lagrangian investigation, two scenarios of local extinction, i.e., severe extinction with lower temperature and moderate extinction with higher temperature, are shown. Meanwhile, two re-ignition mechanisms are distinguished by the explosion index of the process prior to re-ignition. It is found that re-ignition mechanism through premixed flame propagation corresponds to a rather long preheat period with thermal runaway and high temperature explosion index, while re-ignition mechanism via independent flamelet corresponds to a high radical explosion index and small temperature gradient. [ABSTRACT FROM AUTHOR]

In this study, we introduce a Lagrangian drop (LD) model to study warm rain microphysical processes in shallow cumulus. The approach combines Large-Eddy Simulations (LES) including a bulk microphysics parameterization with an LD model for raindrop growth. The LD model is one-way coupled with the Eulerian LES and represents all relevant rain microphysical processes such as evaporation, accretion, and selfcollection among LDs as well as dynamical effects such as sedimentation and inertia. To test whether the LD model is fit for purpose, a sensitivity study for isolated shallow cumulus clouds is conducted. We show that the surface precipitation rate and the development of the raindrop size distribution are sensitive to the treatment of selfcollection in the LD model. Some uncertainty remains for the contribution of the subgrid-scale turbulence to the relative velocity difference of a pair of LDs, which appears as a factor in the collision kernel. Sensitivities to other model parameters such as the initial multiplicity or the initial mass distribution are small. Overall, sensitivities of the LD model are small compared to the uncertainties in the assumptions of the bulk rain microphysics scheme, and the LD model is well suited for particle-based studies of raindrop growth and dynamics. This opens up the opportunity to study effects like recirculation, deviations from terminal fall velocity and other microphysical phenomena that so far were not accessible for bin, bulk, or parcel models. [ABSTRACT FROM AUTHOR]

This paper describes a strategy to solve multi-fluid and fluid-structure interaction (FSI) problems using Lagrangian particles combined with a fixed finite element (FE) mesh. Our approach is an extension of the fluid-only PFEM-2 (Idelsohn et al., Eng Comput 30(2):2-2, ; Idelsohn et al., J Numer Methods Fluids, ) which uses explicit integration over the streamlines to improve accuracy. As a result, the convective term does not appear in the set of equations solved on the fixed mesh. Enrichments in the pressure field are used to improve the description of the interface between phases. [ABSTRACT FROM AUTHOR]

This study investigates how entrainment affects the activation of aerosols in a shallow cumulus cloud using large-eddy simulations (LES) with an embedded Lagrangian cloud model (LCM) in which aerosols and droplets are explicitly treated as Lagrangian particles. The activation process is analyzed for aerosols entrained (i) by the central updraft at cloud base and (ii) by turbulent mixing above cloud base (lateral entrainment). Cloud base aerosols and laterally entrained aerosols contribute to all activated aerosols inside the cloud by fractions of 70% and 30%, respectively. Laterally entrained particles dominate the activation above cloud base (secondary activation), to which cloud base aerosols contribute about one third. As assumed in many parameterizations, the activation of cloud base aerosols is limited by the maximum saturation. However, the activation of laterally entrained aerosols is determined by the degree of turbulence, limiting the time available for activation and restricting the activation to intermediate sized aerosols, which demand the shortest time for activation. As the environmental aerosol concentration increases, activation of laterally entrained aerosols becomes more important. [ABSTRACT FROM AUTHOR]

The occurrence, frequency, and intensity of blade-strike of fish on an axial-flow marine hydrokinetic turbine was simulated using two modeling approaches: a novel scheme combining computational fluid dynamics (CFD) with Lagrangian particle tracking, and a conventional kinematic model. The kinematic model included simplifying assumptions of fish trajectories such as distribution and velocity. The proposed CFD and Lagrangian particle tracking methods provided a more realistic representation of blade-strike mechanisms by integrating the following components: (i) advanced unsteady turbulence simulation using detached eddy simulation (DES), (ii) generation of inflow turbulence based on field data, (iii) moving turbine blades in highly transient flows, and (iv) Lagrangian particles to mimic the potential fish pathways. The test conditions to evaluate the blade-strike probability and fish survival rate were: (i) the turbulence environment, (ii) the fish size, and (iii) the approaching flow velocity. The proposed Lagrangian method simulates potential fish trajectories and their interaction with the rotating turbine with the limitation that it does not include any volitional fish avoidance behavior. Depending upon the scenario, the percentage of particles that registered a collision event ranged from 6% to 19% of the released sample size. Next, by using a set of experimental correlations of the exposure-response for live fish colliding with moving blades, the simulated collision data were used as input variables to estimate the survival rate of fish passing through the operating turbine. The resulting survival rates were greater than 96% in all scenarios, which is comparable to or better than known survival rates for conventional hydropower turbines. The kinematic model predicted higher blade-strike probabilities and mortality rates than the Lagrangian particle-based method did. The Lagrangian method also offers the advantage of expanding the evaluation framework to include additional mechanisms of stress and injury on fish, or other aquatic biota, caused by hydrokinetic turbines and related devices. [ABSTRACT FROM AUTHOR]

The simulation of turbulent flow that involves scalar transport at high Schmidt or Prandtl numbers is a major challenge. Enhanced Schmidt and Prandtl numbers demand an excessive increase in numerical resolution. Otherwise, the accuracy of transport would suffer substantially through unresolved information and numerical diffusion. With the aim of providing an efficient alternative for such applications, this paper presents a simulation method that is based on a novel Eulerian-Lagrangian decomposition principle (ELD) of the transported quantity. Low-pass filtering of the initial scalar quantity field separates it into a smooth low-frequency component and a fine-structured high-frequency component. The low-frequency component is represented and transported according to the Eulerian description by applying the Finite Volume Method (FVM) with a numerical resolution according to the Kolmogorov scale. The high-frequency component is translated into the Lagrangian description by the formation of particles, which are transported in parallel. By exchanging information between the two components, a re-initialisation mechanism ensures that the frequency-based decomposition is maintained throughout the simulation. Such ELD approach combines the efficiency of the FVM with the numerical stability of Lagrangian particles. As a result of the frequency-separation, the latter are by principle limited to zones of small scales and thus effectively complement the FVM. Furthermore, the particle information allows details of the scalar quantity field to be reconstructed that extend into the sub-grid level. By using a mixing layer setup, the proposed method is tested for a range of Schmidt numbers, and the numerical costs are considered and discussed. • The transport of scalar quantities at high Schmidt numbers is becoming an increasingly important phenomenon in science. • Their accurate numerical simulation is extremely costly with the methods and resources that are currently available. • The combination of FVM with particle methods is a promising approach provided that the integration is well designed. • A concentrated use of particles in regions where they provide a substantial gain in resolution ensures numerical efficiency. [ABSTRACT FROM AUTHOR]

Cordeiro Pires, A., Nolasco, R. and Dubert, J., 2013. On the origin of summer upwelled waters in Western Iberian Peninsula As in most eastern boundary systems, on the Western Iberian Margin there is coastal upwelling during summer due to the alongshore northerly winds and the consequent offshore displacement of surface waters. This work addresses the origin of these upwelled waters. Using a regional ocean model, a climatological configuration and a lagrangian particle module that is run backward in time, we trace the trajectory of particles arriving at four coastal areas, delimited by the 200-m isobath, approximately, and at three depths: 20 m, 40 m and 60 m. Each point is traced backward for one month, with arrival dates of June 30, July 30 and August 30, the typical upwelling months. We find out where the particles were on June 1, July 1 and August 1, respectively, how deep they have reached and what distance they have traveled. In general, the points of origin were shallower (in the upper 100 m) for the particles that traveled the greatest distances (up to 500 km). These particles come mostly from the north and trace alongshore pathways at 20-40 km from the coast, i.e., within isobaths 100-200 m, the preferential path of the upwelling-associated equatorward jet. Conversely, particles that originate from deeper levels, down to 600 m, come from shorter distances, approximately 100 km. Some particles originate to the west of their point of upwelling, giving evidence of being dependent on meandering and other mesoscale features, such as offshore eddies and upwelling filaments. [ABSTRACT FROM AUTHOR]

Aquatic life exists between very small passive floating objects such as spores, eggs or seeds which are at the mercy of currents through to animals which swim powerfully enough to overcome most natural currents. There is a corresponding scale of cognitive and sensory capability. Coupling hydrodynamic with Lagrangian particle modelling is well established, as is individual based modelling of animal behaviour. These areas have developed rapidly, due to availability of faster computers. These different disciplines have fundamentally different conceptual frameworks, but the combination of techniques offers an unparalleled opportunity to model swimming animals in water more accurately. More accurate models of dispersion, migration and other spatial dynamics would support a better informed ecosystem management and provide methods to define protected areas that are linked in coherent networks. Development plans for tidal power schemes and offshore wind farms mean that predictive models of migrating fish are needed urgently. Statistical models based on correlations become inaccurate as the environments move to previously unobserved states. This is where models based on rules such as individual based models have a unique advantage. I briefly review Eulerian, Lagrangian, coupled Eulerian–Lagrangian water models, water quality models and individual based models of animal movements, navigation and interactive behaviour. [Copyright &y& Elsevier]

Abstract: Stochastic differential equations (SDEs) offer an attractively simple solution to complex transport-controlled problems, and have a wide range of physical, chemical, and biological applications, which are dominated by stochastic processes, such as diffusion. As for deterministic ordinary differential equations (ODEs), various numerical scheme exist for solving SDEs. In this paper various particle-tracking schemes are presented and tested for accuracy and efficiency (time vs. accuracy). To test the schemes, the particle tracking algorithms are implemented into a community wide used 1D water column model. Modelling individual particles allows a straightforward physical interpretation of the involved processes. Further, this approach is strictly mass conserving and does not suffer from the numerical diffusion that plagues grid-based methods. Moreover, the Lagrangian framework allows to assign properties to the individual particles, that can vary spatially and temporally. The movement of the particles is described by a stochastic differential equation, which is consistent with the advection–diffusion equation. Here, the concentration profile is represented by a set of independent moving particles, which are advected according to the velocity field, while the diffusive displacements of the particles are sampled from a random distribution, which is related to the eddy diffusivity field. The paper will show that especially the 2nd order schemes are accurate and highly efficient. At the same level of accuracy, the 2nd order scheme can be significantly faster than the 1st order counterpart. This gain in efficiency can be spent on a higher resolution for more accurate solutions at a lower cost. [Copyright &y& Elsevier]

Abstract: Pyroclastic density currents (PDCs) vary between two end members, concentrated and dilute. When a PDC interacts with an uneven topography, the flow field variables (velocity, pressure, bulk density, particle concentration) may drastically change near the flow–substrate boundary. These changes may significantly affect the sediment flux and the resulting deposits can record the effects in their facies architecture. Here we show, by means of numerical simulations, how a dilute pyroclastic density current interacts with four different types of simple topography, namely: flat, one hill, one valley and two hills. Our numerical scheme treats the very fine particles as being in full thermo-mechanical equilibrium with the volcanic gas, i.e. a dusty gas. A dusty gas–air mixture is defined as a mixture of dusty gas and atmospheric air. The trajectories of the coarser particles or discrete phase (three grain-size classes of 1mm, 5mm and 10mm and density of 1500kg/m3) are tracked as Lagrangian particles that interact with the dusty gas–air mixture through two-way momentum and energy coupling. Numerical results are used to analyze the local effects of topography on the deposition of the Lagrangian particles, by monitoring with time and space the local changes at the boundary between the current and the substrate. The results show that the sediment flux in the flow boundary zone increases near the stoss sides of hills and in the valleys, relative to the flat reference case, whereas it decreases along the lee flanks and on top of the hills. We use the sediment flux in the flow boundary zone and the grain-size distribution of the Lagrangian particles as proxies of the deposit features, and by these parameters we qualitatively compare simulations with deposits of known eruptions. [ABSTRACT FROM AUTHOR]

Suspended particulate matter (SPM) dynamics in ocean models are usually treated with an advection–diffusion equation for one or more sediment size classes coupled to the hydrodynamical part of the model. Numerical solution of these additional partial differential equations unavoidably introduces numerical diffusion, i.e. in the case of sharp gradients the possible occurrence of artificial oscillations and non-positivity. A Lagrangian particle-tracking model has been developed to simulate short-term SPM dynamics. Modelling individual sediment particles allows a straightforward physical interpretation of the processes. The tracking of large numbers of individual and independent particles (up to 25 million in total in a single sediment class) can be achieved on high performance computer clusters, due to efficient parallelisation of particle tracking. The movement of the particles is described by a stochastic differential equation, which is consistent with the advection–diffusion equation. Here, the concentration profile is represented by a set of independent moving particles, which are advected according to the 3D velocity field, while the diffusive displacements of the particles are sampled from a random distribution, which is related to the eddy diffusivity field. To account for erosion a new parameterisation is proposed. Three numerical particle tracking schemes (EULER, MILSTEIN and HEUN) are presented and validated in idealised test cases. Finally, the particle tracking algorithms are applied to a realistic scenario, a severe winter storm in the East Frisian Wadden Sea (southern North Sea). The comparison with observations and an Eulerian SPM transport model seems to indicate a somewhat better fidelity of the Lagrangian approach. [ABSTRACT FROM AUTHOR]

Abstract: We propose a new numerical method for modeling motion of open curves in two dimensions and open surfaces in three dimensions. Following the grid based particle method we proposed in [S. Leung, H.K. Zhao, A grid based particle method for moving interface problems. J. Comput. Phys. 228 (2009) 2993–3024], we represent the open curve or the open surface by meshless Lagrangian particles sampled according to an underlying fixed Eulerian mesh. The underlying grid is used to provide a quasi-uniform sampling and neighboring information for meshless particles. The key idea in the current paper is to represent and to track end-points of the open curve and boundary-points of the open surface explicitly and consistently with interior particles. We apply our algorithms to several applications including spiral crystal growth modeling and image segmentation using active contours. [Copyright &y& Elsevier]

We give an exponentially accurate normal form for a Lagrangian particle moving in a rotating shallow-water system in the semigeostrophic limit, which describes the motion in the region of an exponentially accurate slow manifold (a region of phase space for which dynamics on the fast scale are exponentially small in the Rossby number). We show how this result is related to the variational asymptotics approach of [M. Oliver, J. Fluid Mech., 551 (2006), pp. 197-234]; the difference is that on the Hamiltonian side it is possible to obtain strong bounds on the growth of fast motion away from (but close to) the slow manifold. Our normal form approach extends to numerical approximations via backward error analysis and extends to particle methods for the shallow-water equations, where the result shows that particles stay close to balance over long times in the semigeostrophic limit. [ABSTRACT FROM AUTHOR]

The flux of energy from large to small scales in hydrodynamic turbulence controls the dissipation of energy at a given scale in the fluid. An accurate parametrization of this flux is a prerequisite in order to devise reliable methods to simulate turbulent flows without resolving all the scales of motion. This problem is discussed in the context of a particle method based on the Smooth Particles Hydrodynamics algorithm. Motivated by the von Karman–Howarth–Kolmogorov exact relation for the energy flux, and by Lagrangian dynamics considerations we postulate an energy transfer term which is quadratic in the velocity and formally time reversal invariant. The numerical simulation of the model however is observed to spontaneously break the time reversal symmetry, demonstrating that the proposed term acts on average as the desired eddy damping. [ABSTRACT FROM AUTHOR]

We adapt a continuous data assimilation scheme, known as the Azouani–Olson–Titi (AOT) algorithm, to the case of moving observers for the 2D incompressible Navier–Stokes equations. We propose and test computationally several movement patterns (which we refer to as "the bleeps, the sweeps and the creeps"), as well as Lagrangian motion and combinations of these patterns, in comparison with static (i.e. non-moving) observers. In several cases, order-of-magnitude improvements in terms of the time-to-convergence are observed. We end with a discussion of possible applications to real-world data collection strategies that may lead to substantial improvements in predictive capabilities. • 2D Navier–Stokes flow is captured well by data assimilation with moving observers. • Moving observers during data assimilation dramatically improves convergence rates. • Far fewer observers are needed if observers move in certain patterns. • Several movement patterns clearly outperform others; reasons for this are explored. [ABSTRACT FROM AUTHOR]