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The aim of this work was to analyze the influence of sex hormones and anatomical details (trabeculations and false tendons) on the electrophysiology of healthy human hearts. Additionally, sex- and anatomy-dependent effects of ventricular tachycardia (VT) inducibility are presented. To this end, four anatomically normal, human, biventricular geometries (two male, two female), with identifiable trabeculations, were obtained from high-resolution, ex-vivo MRI and represented by detailed and smoothed geometrical models (with and without the trabeculations). Additionally one model was augmented by a scar. The electrophysiology finite element model (FEM) simulations were carried out, using O’Hara-Rudy human myocyte model with sex phenotypes of Yang and Clancy. A systematic comparison between detailed vs smooth anatomies, male vs female normal hearts was carried out. The heart with a myocardial infarction was subjected to a programmed stimulus protocol to identify the effects of sex and anatomical detail on ventricular tachycardia inducibility. All female hearts presented QT-interval prolongation however the prolongation interval in comparison to the male phenotypes was anatomy-dependent and was not correlated to the size of the heart. Detailed geometries showed QRS fractionation and increased T-wave magnitude in comparison to the corresponding smoothed geometries. A variety of sustained VTs were obtained in the detailed and smoothed male geometries at different pacing locations, which provide evidence of the geometry-dependent differences regarding the prediction of the locations of reentry channels. In the female phenotype, sustained VTs were induced in both detailed and smooth geometries with RV apex pacing, however no consistent reentry channels were identified. Anatomical and physiological cardiac features play an important role defining risk in cardiac disease. These are often excluded from cardiac electrophysiology simulations. The assumption that the cardiac endocardium is smooth may produce inaccurate predictions towards the location of reentry channels in in-silico tachycardia inducibility studies JA-S, FS, GH and MV are supported by the European Union’s Horizon 2020 research and innovation programme under grant agreements No 675451 (Compbiomed project phase 1) and No 823712 (CompBioMed project, phase 2) and project No 777204 (SilicoFCM project). Part of the simulation computing hours were provided by the CompBioMed project phase 1. JA-S was awarded computation time from Red Espanola de Supercomputacion (RES). (Activity IDs: FI-2018-2-0049 and BCV-2019-2-0014) JA-S is funded by a Ramon y Cajal fellowship (RYC-2017-22532), Ministerio de Ciencia e Innovacion, Spain; and by Plan Estatal de Investigacion Cientifica y Tecnica y de Innovacion 2017-2020 from the Ministerio de Ciencia e Innovacion y Universidades (PID2019-104356RBC41/AEI/10.13039/501100011033): meHeart ME PID2019-104356RB-C44. CB is funded by the Torres Quevedo Program (PTQ2018-010290), Ministerio de Ciencia e Innovacion, Spain. MV, GH and CB are funded by the Spanish Neotec project EXP - 00123159/SNEO-20191113 Generador de corazones virtuales. LKGM was funded by Fundacion Carolina-BBVA. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. There was no additional external funding received for this study. Peer Reviewed "Article signat per 11 autors/es: Pablo Gonzalez-Martin,Federica Sacco,Constantine Butakoff,Ruben Doste,Carlos Bederian,Lilian K. Gutierrez Espinosa de los Monteros,Guillaume Houzeaux,Paul A. Iaizzo,Tinen L. Iles,Mariano Vazquez,Jazmin Aguado-Sierra"

This document feeds research and development priorities devel-oped by the European HPC ecosystem into EuroHPC’s Research and Innovation Advisory Group with an aim to define the HPC Technology research Work Programme and the calls for proposals included in it and to be launched from 2023 to 2026. This SRA also describes the major trends in the deployment of HPC and HPDA methods and systems, driven by economic and societal needs in Europe, taking into account the changes ex-pected in the technologies and architectures of the expanding underlying IT infrastructure. The goal is to draw a complete picture of the state of the art and the challenges for the next three to four years rather than to focus on specific technologies, implementations or solutions. Peer Reviewed Article signat per 140 autors/autores: Estela Suarez,JSC; Nico Mittenzwey, MEGWARE; Laurent Cargemel, Atos; Alessandro Russo, Leonardo; Andy Forrester, HypeAccelerator Solutions Limited; Carlo Cavazzoni, Leonardo; Craig Prunty, SiPearl; Daniele Cesarini, Cineca; David Tur, Do IT Now; Fabrizio Magugliani, E4 Computer Engineering SpA; Marc Casas, BSC; Rene Oertel, MEGWARE Computer Vertrieb und Service GmbH; Sergio Sánchez, Vicomtech; Thierry Porcher, Do IT Now; Marc Duranton, CEA / HiPEAC; Sakir Sezer, NVIDIA; Craig Prunty, SIPEARL; Alessandro Russo, Leonardo; Dirk Pleiter, KTH; Luigi Capone, Leonardo; Marco Cicala, E4 Computer Engineering SpA; Osman Unsal, BSC; Paolo Amato, Micron; Petar Radojkovic, BSC; Rod Evans, NVIDIA; Thierry Porcher, Do IT Now; Xavier Martorell, BSC; Manolis Marazakis, FORTH; Maria Perez, UPM / BDVA; Pascale Rossé-Laurent, Atos; Alberto Miranda, BSC; Alberto Scionti, LINKS Foundation; Alessandro Russo, Leonardo; David Tur, Do IT Now; Denis Maggi, Vicomtech; Georgios Goumas, ICCS; Ina Schmitz, ParTec; Jordi Guitart, BSC; Julita Corbalan, BSC; Michele Martone, LRZ; Nico Mittenzwey, MEGWARE; Nicolo Magini, Leonardo; Paolo Viviani, LINKS Foundation; Rene Oertel, MEGWARE Computer Vertrieb und Service GmbH; Sebastien Varrette, University of Luxembourg; Thierry Porcher, Do IT Now; Thomas Moschny, Par-Tec, Guy Lonsdale, SCAPOS; Paul Carpenter, BSC; Gabriel Antoniu, INRIA (BDVA); Alexander Costan, INSA Rennes/Inria; Ani Anciaux Sedrakian, IFPEN; Antonio Peña, BSC; Antonio Sciarappa, Leonardo; Christian Perez, INRIA; Francesco Iannone, ENEA; Jose Gracia, HLRS; Leonardo Arturo Bautista Gomez, BSC; Luigi Capone, Leonardo; Miguel Vasquez, BSC; Olivier Marsden, ECMWF; Paolo Viviani, LINKS Foundation; Patrick Carribault, CEA; Sebastien Varrette, University of Luxembourg; Vicenc Beltran, BSC; Xavier Martorell, BSC; Andre Brinkmann, JGU – Mainz; Sai Narasimhamurthy, Seagate; Anna Queralt, BSC; Jean-Thomas Acquaviva, DDN Storage; Jesús Carretero Pérez, UC3M; Nicolo Magini, Leonardo Labs; Paolo Amato, Micron; Philippe Deniel, CEA; Ramon Nou, BSC; Tiago Quintino, ECMWF; Dirk Pleiter, KTH; Utz-Uwe Haus, HPE; Adrian Tate, NAG; Ani Anciaux Sedrakian, IFPEN; Antonio Sciarappa, Leonardo Labs; Chiara Vercellino, LINKS Foundation; Dario Garcia-Gasulla, BSC; Giovanni Samaey, KU Leuven; Luigi Capone, Leonardo; Marcin Chrust, ECMWF; Maximilian Behr, Northern Data AG, Olivier Beaumont, INRIA; Ricard Borrell, BSC; Ulrich Ruede, CERFACS/FAU; Ward Melis, KU Leuven; Erwin Laure, MPCDF; Andreas Wierse, SICOS; Bruno Raffin, INRIA; Carlo Cavazzoni, Leonardo; Guillaume Houzeaux, BSC; Ioan Hadade, ECMWF; Kim Serradell Maronda, BSC; Luigi Capone, Leonardo; Miguel Vasquez, BSC; Ricard Borrell, BSC; Sabri Pllana; Sinead Ryan, Trinity College Dublin; Vicence Beltran, BSC; Hans-Christian Hoppe, ParTec; Jens Krueger, FRAUNHOFER; Alberto Scionti, LINKS Foundation; Ander Garcia, Vicomtech; Anna Queralt, BSC; Benjamin Depardon, UCit; Craig Prunty, SIPEARL; Daniela Ghezzim, Leonardo S.p.a.; Daniele Piccarozzi, Arm; David Carrera, BSC; Philippe Bricard, UCit; Thierry Goubier, CEA; Venkatesh Kannan, ICHEC; Valeria Bartsch, FRAUNHOFER; Cyril Allouche, Atos; Kristel Michelsen, JSC; Andrea Scarabosio, Links Foundation; Artur Garcia, BSC; Chayma Bouazza, PASQAL; Daniele Dragoni, Leonardo; Daniele Gregori, E4 Computer Engineering SpA; Daniele Ottaviani, Cineca; David Bowden, Dell Technologies; David Tur, Do IT Now; Dennis Hoppe, High-Performance Computing Center Stuttgart; Fabrizio Magugliani,E4 Computer Engineering SpA; Filippo Palombi, ENEA; Giacomo Vitali, LINKS Foundation; Guillaume Colin de Verdière, CEA; Jean-Philippe Nominé, CEA; Leonardo Arturo Bautista Gomez, BSC; Mikael Johansson, CSC; Olivier Terzo, LINKS Foundation; Osman Unsal, BSC; Vekatesh KannanI, CHEC; Erwin Laure, MPCDF; Andreas Wierse, SICOS; Bruno Raffin, INRIA; Carlo Cavazzoni, Leonardo; Guillaume Houzeaux, BSC; Ioan Hadade, ECMWF; Kim Serradell Maronda, BSC; Luigi Capone, Leonardo; Miguel Vasquez, BSC; Ricard Borrell, BSC; Sabri Pllana Sinead Ryan, Trinity College Dublin; Vicence Beltran, BSC; Hans-Christian Hoppe, ParTec; Jens Krueger, FRAUNHOFER; Alberto Scionti, LINKS Foundation; Ander Garcia, Vicomtech; Anna Queralt, BSC; Benjamin Depardon, UCit; Craig Prunty, SIPEARL; Daniela Ghezzi, Leonardo S.p.a.; Daniele Piccarozzi, Arm; David Carrera, BSC; Philippe Bricard, UCit; Thierry Goubier, CEA; Venkatesh Kannan, ICHEC; Valeria Bartsch, FRAUNHOFER; Cyril Allouche, Atos; Kristel Michelsen, JSC; Andrea Scarabosio, Links Foundation; Artur Garcia, BSC; Chayma Bouazza, PASQAL; Daniele Dragoni, Leonardo Daniele Gregori, E4 Computer Engineering SpA; Daniele Ottaviani, Cineca; David Bowden, Dell Technologies; David Tur, Do IT Now; Dennis Hoppe, High-Performance Computing Center Stuttgart; Fabrizio Magugliani, E4 Computer Engineering SpA; Filippo Palombi, ENEA; Giacomo Vitali, LINKS Foundation; Guillaume Colin de Verdière, CEA; Jean-Philippe Nominé, CEA Leonardo; Arturo Bautista Gomez, BSC, Mikael Johansson, CSC; Olivier Terzo, LINKS Foundation; Osman Unsal, BSC; Vekatesh KannanI; Utz-Uwe Haus (HPE); Sai Narasimhamurthy (Seagate); Maria S. Perez (UPM); Dirk Pleiter (KTH); Andreas Wierse (SICOS); Paul Carpenter (BSC); Utz-Uwe Haus (HPE); Erwin Laure (MPCDF); Sai Narasimhamurthy (Seagate Systems); Estela Suarez (Forschungszentrum Jülich); Manolis Marazakis (FORTH); Marc Duranton (CEA); Dirk Pleiter (KTH); Giuliano Taffoni (INAF); Hans-Christian Hoppe (Scapos AG); Gabriel Antoniu (Inria); Patrick Valduriez (Inria); Hans-Christian Hoppe (SCAPOS); Jens Krüger (Fraunhofer ITWM); Andreas Wierse (Sicos BW); François Bodin (Inria); Sagar Dolas (SURF); Damien Gratadour (Université Paris Diderot); Michael Malms (ETP4HPC); Leonieke Mevus (SURF); Pascale Rossé-Laurent (Atos); Jean-Robert Bacou (Atos); Carlos Puchol (BSC); Kristel Michielsen (JSC); Tiina Leiponen (CSC); Carlo Cavazzoni (Leonardo), Ivan Spisso (Leonardo); Maike Gilliot (ETP4HPC); Hans-Christian Hoppe (Scapos); Guy Lonsdale (ETP4HPC Steering Board / Fraunhofer / Scapos / FocusCoE); Fabrizio Magugliani (ETP4HPC Steering Board / E4 Computer Engineering); Jean-Philippe Nominé (ETP4HPC Steering Board / CEA); Andreas Wierse (SICOS); Pascal Bouvry (University of Luxembourg); Daniela Posch (SICOS); Gilles Civario (Intel); Henri Calandra (TotalEnergies & PRACE IAC); Vincent Galinier (Airbus & PRACE IAC); Xavier Vigouroux (Atos); Alban Rousset (LuxProvide); Michael Schlottke-Lakemper (HLRS); Carolina Berucci (Leonardo), Erwin Laure, Carolina Berucci (Leonardo)

With the increase in computational power in the last decade and the forthcoming Exascale supercomputers, a new horizon in computational modelling and simulation is envisioned in combustion science. Considering the multiscale and multiphysics characteristics of turbulent reacting flows, combustion simulations are considered as one of the most computationally demanding applications running on cutting-edge supercomputers. Exascale computing opens new frontiers for the simulation of combustion systems as more realistic conditions can be achieved with high-fidelity methods. However, an efficient use of these computing architectures requires methodologies that can exploit all levels of parallelism. The efficient utilization of the next generation of supercomputers needs to be considered from a global perspective, that is, involving physical modelling and numerical methods with methodologies based on High-Performance Computing (HPC) and hardware architectures. This review introduces recent developments in numerical methods for large-eddy simulations (LES) and direct-numerical simulations (DNS) to simulate combustion systems, with focus on the computational performance and algorithmic capabilities. Due to the broad scope, a first section is devoted to describe the fundamentals of turbulent combustion, which is followed by a general description of state-of-the-art computational strategies for solving these problems. These applications require advanced HPC approaches to exploit modern supercomputers, which is addressed in the third section. The increasing complexity of new computing architectures, with tightly coupled CPUs and GPUs, as well as high levels of parallelism, requires new parallel models and algorithms exposing the required level of concurrency. Advances in terms of dynamic load balancing, vectorization, GPU acceleration and mesh adaptation have permitted to achieve highly-efficient combustion simulations with data-driven methods in HPC environments. Therefore, dedicated sections covering the use of high-order methods for reacting flows, integration of detailed chemistry and two-phase flows are addressed. Final remarks and directions of future work are given at the end. } The research leading to these results has received funding from the European Union’s Horizon 2020 Programme under the CoEC project, grant agreement No. 952181 and the CoE RAISE project grant agreement no. 951733.

GPUs have climbed up to the top of supercomputer systems making life harder to many legacy scientific codes. Nowadays, many recipes are being used in such code's portability, without any clarity of which is the best option. We present a comparative analysis of the two most common approaches, CUDA and OpenACC, into the multi-physics CFD code Alya. Our focus is the combustion problems which are one of the most computing demanding CFD simulations. The most computing-intensive parts of the code were analyzed in detail. New data structures for the matrix assembly step have been created to facilitate a SIMD execution that benefits vectorization in the CPU and stream processing in the GPU. As a result, the CPU code has improved its performance by up to 25%. In GPU execution, CUDA has proven to be up to 2 times faster than OpenACC for the assembly of the matrix. On the contrary, similar performance has been obtained in the kernels related to vector operations used in the linear solver, where there is minimal memory reuse.

The Conditional Moment Closure (CMC), devised for turbulent combustion modelling, was implemented in the multiphysics code Alya, based on the Finite Element Method (FEM), in the frame of Large Eddy Simulations (LES) for unstructured meshes. A multi-code approach has been developed to run separately the transport equations for non-reacting variables (CFD) and the conditioned quantities (CMC) in two different meshes. The fundamental aspects of the algorithm are discussed while a new strategy for the interpolation between CFD and CMC meshes is described. The Cambridge swirling burner is analysed and simulations results are compared to measurements. The research leading to these results has received funding from the Clean Sky 2 Joint Undertaking under the European Union’s Horizon 2020 research and innovation programme under the ESTiMatE project, grant agreement No 821418.

This study is focused on the numerical investigation of reduced chemical schemes for high pressure spray flames of oxymethylene ethers (OMEx). A reduced mechanism using Path Flux Analysis (PFA) technique is tested using an a priori and a posteriori evaluation under the ECN Spray A nominal conditions. The global flame metrics for spray A along with the flame shape are well reproduced by the reduced mechanism, which encourages its use for practical applications. The research leading to these results has received funding through the ENERXICO project from the European Union’s Horizon 2020 Programme, grant agreement n 828947, and from the Mexican Department of Energy, CONACYT-SENER Hidrocarburos grant agreement n B-S-69926 and the Spanish Ministry of Economy and Competitiveness in the frame of the CHEST project (TRA2017-89139-C2-2- R). The authors thankfully acknowledge the computer resources at MareNostrum and the technical support provided by Barcelona Supercomputing Center (IM- 2021-1-0014, IM-2020-3-0029, IM-2020-2-0023,IM- 2020-1-0013).

This work presents a numerical study of a technically premixed swirling combustor with central air injection at conditions close to flashback using large-eddy simulation with flamelet modelling. This burner has the characteristics of showing flashback at low equivalence ratios, so numerical simulations are set to identify the mechanisms behind the flashback formation. Experimental findings suggest the axial momentum ratio between fuel and air dominates the flame stabilization mechanism and flashback resistance over mixing and equivalence ratio fluctuations. This aspect is investigated here for two operating conditions with the same axial momentum ratio as in the experiment using a perfectly premixed assumption. The two test cases correspond to two stable operating points, far and close to the flashback point. The study shows the assumption of perfect premixing is valid during the stable operation of the burner up to flashback conditions. The experimental results are well predicted under inert and reacting conditions by using a perfectly premixed mixture. It is found that the non reacting flow field develops a self-excited oscillation in the form of a precessing vortex core. This oscillation is attenuated by the fuel injection due to the respective increase in axial momentum and it is ultimately suppressed in the reacting flow field. Both experiments and simulations confirm the same trends. The analysis of the flames have shown certain dynamics as the flashback point is approached. The flashback resistance of the burner is minimized due to an increase in the velocity deficit of the incoming mixture. The recirculation region is shifted upstream, the central recirculation is altered and the flame position is displaced towards the inlet of the reactants in the combustion chamber. The analysis of instabilities and flow dynamics suggest that the formation of flashback can be attributed to combustion induced vortex breakdown, which in turn is associated to the lower axial momentum introduced by the fuel jets in leaner conditions. The research leading to these results has received funding through the Spanish Ministry of Economy and Competitiveness in the frame of the CHEST project (TRA2017- 89139-C2-2-R). Conflict of Interest: Daniel Mira acknowledges the Juan de la Cierva personal grant IJCI-2015-26686 and Ambrus Both the Marie Skłodowska-Curie grant agreement No. 713673 through the ”la Caixa” INPhINIT Fellowship Grant. Computer resources and technical assistance has been provided by the Red Española de Supercomputación (RES) and the Gauss Centre for Supercomputing e.V. (www.gauss-centre.eu) on the GCS Supercomputer SuperMUC at Leibniz Supercomputing Centre (www.lrz.de). The TU Berlin would like to acknowledge the funding received from the EU Seventh Framework Program (FP7/2007-2013) under GA284636 and the European Research Council under the ERC GREENEST with GA247322.

High Performance Computing (HPC) applications are highly complex and demand ecient execution. Energy require- ment of current petascale and future exascale systems is a major cause for concern, and it is crucial to improve the energy-eciency of the applications that run on these systems. A signi cant source of improvement for applications is that they commonly exhibit dynamic resource requirements. Consequently, such dynamism in an application presents opportunity to tailor the utilisation of resources in the HPC system based on the requirements of the application at runtime. READEX (Runtime Exploitation of Application Dynamism for Energy-ecient eXascale computing) is a EU Horizon 2020 FET-HPC project whose objective is to exploit the dynamism found in HPC applications at runtime to achieve ecient computation on exascale systems. Alya is a high performance computational mechanics application that is present in the Uni ed European Application Benchmark Suite and the PRACE Accelerator Benchmark Suite. In this paper, we apply the READEX methodology on Alya to identify and exploit any dynamism that is exhibited. We report on the potential energy savings and the e ects on the application runtime, where we observe 5-20% reduction in the energy consumed by the application.

This work investigates the accuracy and performance of a FE2 multi-scale implementation used to predict the behavior of composite materials. The equations are formulated assuming the small deformations solid mechanics approach in non-linear material models with hardening plasticity. The uniform strain boundary conditions are applied for the macro-to-micro transitions. A parallel algorithm was implemented in order to solve large engineering problems. The scheme proposed takes advantage of the domain decomposition method at the macro-scale and the coupling between each subdomain with a micro-scale model. The precision of the method is validated with a composite material problem and scalability tests are performed for showing the efficiency.

This paper deals with the definition of the lube-oil film thickness in the piston ringcylinder liner junction of an internal combustion engine. At first, a mathematical modelfor the estimation of the film thickness is established. It is used to point out the oscillating motion of the piston ring normal to the cylinder wall. For the first time, has beenhighlighted and analytically evaluated the oscillating behavior of the piston ring in itshousing in the radial direction. Furthermore, it is demonstrated that the radial oscillations frequency is a function of piston ring stiffness, material and geometry.

Computational fluid dynamics (CFD) is the main field of computational mechanics that has historically benefited from advances in high-performance computing. High-performance computing involves several techniques to make a simulation efficient and fast, such as distributed memory parallelism, shared memory parallelism, vectorization, memory access optimizations, etc. As an introduction, we present the anatomy of supercomputers, with special emphasis on HPC aspects relevant to CFD. Then, we develop some of the HPC concepts and numerical techniques applied to the complete CFD simulation framework: from preprocess (meshing) to postprocess (visualization) through the simulation itself (assembly and iterative solvers).

In this contribution, preliminary results on the study of the VIV at high Reynolds numbers are presented. First, a validation of the code and the turbulent LES WALE formulation in conjunction with a low-dissipative discretization is presented by means of the study of the smooth static cylinder at sub-critical and critical regimes: Re = 1.1 x 10 4 and and Re = 3 x 10 5. Finally, some results of the forced damped oscillating cylinder for the Re = 1.1 x 10 4 case are shown. One of the main objectives of this project is to analyse how the movement of the cylinder affects the sub-critical and critical regimes and the influence of this changes in the aerodynamics forces at high Reynolds numbers present in industrial applications.

As one of the results of an ambitious project, this handbook provides a well-structured directory of globally available software tools in the area of Integrated Computational Materials Engineering (ICME). The compilation covers models, software tools, and numerical methods allowing describing electronic, atomistic, and mesoscopic phenomena, which in their combination determine the microstructure and the properties of materials. It reaches out to simulations of component manufacture comprising primary shaping, forming, joining, coating, heat treatment, and machining processes. Models and tools addressing the in-service behavior like fatigue, corrosion, and eventually recycling complete the compilation. An introductory overview is provided for each of these different modelling areas highlighting the relevant phenomena and also discussing the current state for the different simulation approaches. A must-have for researchers, application engineers, and simulation software providers seeking a holistic overview about the current state of the art in a huge variety of modelling topics. This handbook equally serves as a reference manual for academic and commercial software developers and providers, for industrial users of simulation software, and for decision makers seeking to optimize their production by simulations. In view of its sound introductions into the different fields of materials physics, materials chemistry, materials engineering and materials processing it also serves as a tutorial for students in the emerging discipline of ICME, which requires a broad view on things and at least a basic education in adjacent fields.

Vortex-Bladeless is a Spanish SME whose objective is to develop a new concept of wind turbine without blades called Vortex or vorticity wind turbine. This design represents a new paradigm in wind energy and aims to eliminate or reduce many of the existing problems in conventional generators. Due to the significant difference in the project concept, its scope is different from conventional wind turbines. It is particularly suitable for offshore configuration and it could be exploited in wind farms and in environments usually closed to existing ones due to the presence of high intensity winds. The device is composed of a single structural component, and given its morphological simplicity, its manufacturing, transport, storage and installation has clear advantages. The new wind turbine design has no bearings, gears, etcetera, so the maintenance requirements could be drastically reduced and their lifespan is expected to be higher than traditional wind turbines. It is clear that the proposed device is of prime interest, and that scientific investigation of the response of this wind energy generator under different operation scenarios is highly desirable. Thus, the objective of this SHAPE project is to develop the needed tools to simulate Fluid-Structure Interaction (FSI) problems and to reproduce the experimental results for scaled models of the Vortex-Bladeless device. In order to do so the Alya code, developed at the Barcelona Supercomputing Center, is adapted to perform the Fluid-Structure Interaction (FSI) problem simulation. The obtained numerical results match satisfactorily with the experimental results reported. This work was financially supported by the PRACE project funded in part by the EU’s Horizon 2020 research and innovation programme (2014-2020) under grant agreement 653838.

As one of the results of an ambitious project, this handbook provides a well-structured directory of globally available software tools in the area of Integrated Computational Materials Engineering (ICME). The compilation covers models, software tools, and numerical methods allowing describing electronic, atomistic, and mesoscopic phenomena, which in their combination determine the microstructure and the properties of materials. It reaches out to simulations of component manufacture comprising primary shaping, forming, joining, coating, heat treatment, and machining processes. Models and tools addressing the in-service behavior like fatigue, corrosion, and eventually recycling complete the compilation. An introductory overview is provided for each of these different modelling areas highlighting the relevant phenomena and also discussing the current state for the different simulation approaches. A must-have for researchers, application engineers, and simulation software providers seeking a holistic overview about the current state of the art in a huge variety of modelling topics. This handbook equally serves as a reference manual for academic and commercial software developers and providers, for industrial users of simulation software, and for decision makers seeking to optimize their production by simulations. In view of its sound introductions into the different fields of materials physics, materials chemistry, materials engineering and materials processing it also serves as a tutorial for students in the emerging discipline of ICME, which requires a broad view on things and at least a basic education in adjacent fields.

Domain decomposition methods (DDM) are often chosen to precondition sparse linear systems of equations, as they are famous to well-improve the convergence of iterative solvers. But at the same time, they are difficult to implement and can be computationally expensive. In this work a new mesh numbering to adapt preconditioning techniques to the physics of different problems is proposed as an alternative to DDM preoconditioning.

This work presents a parallel iterative method for numerical solving frictionless contact problem for two elastic bodies. Each iterative step consists of a Dirichlet problem for the one body and a Neumann problem for the other in order to enforce the contact boundary conditions.

A first version of a cardiovascular coupled model is presented. The modelling tools are Alya, the BSC tool for biomechanical simulations; and ADAN55, the LNCC model of the arterial blood flow. The former solves the heartbeat by Finite Element Method (FEM). The latter is a 1D model of the arterial blood flow in a 55-branched geometry. Previous generations of the involved models had fixed boundary conditions. With this novel tool a feedbacked cardiac-vascular model is obtained, offering more physiological boundary conditions and providing further insight in the cardiac-systemic interactions.

The Alya System is the BSC simulation code for multi-physics problems [1]. It is based on a Variational Multiscale Finite Element Method for unstructured meshes. Work distribution is achieved by partitioning the original mesh into subdomains (submeshes). This pre-partition step has until now been done in serial by only one process, using the metis library [2]. This is a huge bottleneck when larger meshes with millions of elements have to be partitioned. This is due to the data not fitting in the memory of a single computing node and in the cases where the data does fit; Alya takes too long in the partitioning step. In this document we explain the tasks done to design, implement and test a new parallel partitioning algorithm for Alya. In this algorithm a subset of the workers, is in charge of partition the mesh in parallel, using the parmetis library [3]. Partitioning workers, load consecutive parts of the main mesh, with a parallel space partitioning bin structure [4], capable of obtaining the adjacent boundary elements of their respective submeshes. With this local mesh, each of the partitioning workers is able to create its local element adjacency graph and to partition the mesh. We have validated our new algorithm using a Navier-Stokes problem on a small cube mesh of 1000 elements. Then we performed a scalability test on a 30M element mesh to check if the time to partition the mesh is reduced proportionally with the number of partitioning workers. We have also done a comparison between metis and parmetis, the balancing of the element distribution among the domains, to test how the use of many partitioning workers to partition the mesh affects the scalability of Alya. We have noticed in these tests that it’s better to use fewer partitioning workers to partition the mesh. Finally we have two sections explaining the results and the future work that has to be done in order to finalise and improve the parallel partition algorithm. This work was financially supported by the PRACE project funded in part by the EUs 7th Framework Programme (FP7/2007-2013) under grant agreement no. RI-312763.

The presented study is a preliminary test and analysis of the role of trabeculae and papillary muscles in the hemodynamics of the left ventricle (LV).

In this work we present a methodology to extract information from medical imaging and use it for hemodynamical simulation in arteries. Based on in-vivo magnetic resonance images (MRI), the velocity of the blood flow has been measured at different positions and times. Also, the anatomy of the vessel has been converted into a volume mesh suitable for numerical modeling. This data has been used to solve computationally the dynamics of the fluid inside the artery in healthy and pathologic cases. As an application, we have developed a computational model within the carotids. The next step in the pipeline will be to extend the simulation to fluidstructure interaction (FSI) to find the parameters in an atherosclerotic plaque that could lead to rupture.

Alya is the BSC in-house HPC-based multi-physics simulation code. It is designed from scratch to run efficiently in parallel supercomputers, solving coupled problems. The target domain is engineering, with all its particular features: complex geome- tries and unstructured meshes, coupled multi-physics with exotic coupling schemes and Physical models, ill-posed problems, flexibility needs for rapidly including new models, etc. Since its conception in 2004, Alya has shown scaling behaviour in an increasing number of cores. In this paper, we present its performance up to 100.000 cores in Blue Waters, the NCSA supercomputer. The selected tests are representative of the engineering world, all the problematic features included: incompressible flow in a hu- man respiratory system, low Mach combustion problem in a kiln furnace and coupled electro-mechanical problem in a heart. We show scalability plots for all cases, discussing all the aspects of such kind of simulations, including solvers convergence., Preprint. Paper submitted to International Supercomputing Conference 2014. Waiting for approval

Alya is a Computational Mechanics (CM) code developed at Barcelona Supercomputing Center, which solves Partial Differential Equations (PDEs) in non-structured meshes, using Finite Element (FE) methods. Being a large scale scientific code, Alya demands substantial I/O processing, which may consume considerable time and can therefore potentially reduce speed-up at petascale. Consequently, I/O task turns out a critical key-point to consider in achieving desirable performance levels. The current Alya I/O model is based on a master-slave approach, which limits scaling and I/O parallelization. However, efficient parallel I/O can be achieved using freely available middleware libraries that provide parallel access to disks. The HDF5 parallel I/O implementation shows a relatively low complexity of use and a wide number of features compared to others implementations, such as MPI-IO and netCDF. Furthermore, HDF5 exposes some interesting aspects such as a shorter development cycle, a hierarchical data format with metadata support and is becoming a de facto standard as well. Moreover, in order to achieve an open-standard format in Alya, the XDMF approach (eXtensible Data Model Format) has been used as metadata container (light data) in cooperation with HDF5 (heavy data). To overcome the I/O barrier at petascale, XDMF & HDF5 have been introduced in Alya and compared to the original master-slave strategy. Both versions are deployed, tested and measured on Curie and Jugene Tier-0 supercomputers. Our preliminary results on the testbed platforms show a clear improvement of the new parallel I/O compared with the original implementation.

This document reports on the construction of a benchmark suite, to be used both within the current PRACE project and beyond, when actual Tier-0 systems will be purchased. Apart from the benchmark suite, this document also reports on currently available performance analysis tools and synthetic benchmarks, as these are essential tools for monitoring scalability and optimisation of benchmark codes, and for analysing and comparing the basic components of HPC systems. This document takes its input from various sources. First, there is the list of applications and their requirements, as delivered by tasks 6.1 and 6.2. As these applications belong to the most frequently used on current European HPC platforms, they should form the basis of a PRACE benchmark suite. Secondly, there is the hardware architecture survey, as conducted by WP7 and its consequences for prototype systems to be used within PRACE. As these prototype architectures are considered as important, it makes sense to use these as platforms for benchmark preparations on scalability (to be handled by task 6.4) and optimisation (task 6.5). A third aspect is the available combinations of expertise on applications and expertise on architecture, for which it makes sense to be used as appropriate and efficient as possible. PRACE targets towards a European research Infrastructure, ideally consisting of various hardware architectures. This implicitly means that some applications are more suited to certain architectures than others. This needs to be reflected in the final benchmark suite, with the idea that potentially subsets of the overall benchmark suite may be used for benchmarking different architectures. These aspects together lead to the output as described in this document, which consists of an initial benchmark suite, with applications ported to target architectures, including recommendations on further work and effort estimates for petascaling (task 6.4) and optimisation (task 6.5). Integration of the benchmark codes into a benchmark suite is an important subtask, as it ensures that other tasks and workpackages within PRACE can use the benchmark suite as their starting point. Identification and categorisation of performance analysis tools and synthetic benchmarks is included as well, especially to be used when tasks 6.4 and 6.5 take off. The document and the initial benchmark suite form a strong basis for this future work.

El método de descomposición de dominios (DD) que se propone en esta tesis pretende resolver flujos incompresibles alrededor de objetos en movimiento relativo. El algoritmo de DD está basado en un acoplamiento del tipo Dirichlet/Neumann(Robin) aplicado a subdominios con solapamiento, y es, por tanto, una extensión del método Dirichlet/Neumann(Robin) clásico con subdominios disjuntos. En realidad, el campo de aplicación de este estudio es mucho más amplio puesto que en el se propone un posible marco teórico para abordar la extensión a subdominios solapados de los métodos mixtos clásicos: métodos Dirichlet/Robin, Dirichlet/Neumann, Robin/Neumann y Robin/Robin. Se observa que los métodos mixtos propuestos heredan propiedades del método de Schwarz y al mismo tiempo conservan el comportamiento de sus equivalentes sin solapamiento cuando este tiende a cero. Se muestra como resultado principal que el solapamiento hace estos métodos más robustos que los métodos sin solapamiento. El método de DD que se estudia es geométrico y algorítmico. Es geométrico en el sentido de que la partición del dominio computacional se lleva a cabo antes del proceso de mallado y de acuerdo con el acoplamiento de DD que se prevé usar. Es también algorítmico porque la solución en cada subdominio se obtiene en procesos diferentes y el intercambio de información entre subdominios se realiza mediante un código maestro. Tal estrategia es muy flexible puesto que requiere muy pocas modificaciones del código numérico original. Por consiguiente, sólo el código maestro necesita ser adaptado a los códigos y estrategias numéricos utilizados en cada subdominio. Se presenta una descripción detallada de la implementación del método de DD propuesto en el contexto numérico de los elementos finitos. Presentamos técnicas de interpolación para los datos de tipo Dirichlet y Neumann y desarrollamos algoritmos de conservación. Una vez el acoplamiento de DD y las interpolaciones definidos, presentamos un método del tipo Chimera para la resolución de flujos alrededor de objetos en movimiento. En particular, definimos transformaciones tensoriales para transformar variables de un subdominio a otro. Finalmente, el algoritmo de DD se aplica a un código implícito para la resolución de las ecuaciones de Navier-Stokes incompresibles y también a las ecuaciones de Navier-Stokes promediadas con un modelo de turbulencia de una ecuación., The domain decomposition (DD) method we present in this work aims at solving incompressible flows around objects in relative motion. The DD algorithm is based on a Dirichlet/Neumann(Robin) coupling applied to overlapping subdomains. Hence, it is an extension of the classical Dirichlet/Neumann(Robin) method which uses disjoint subdomains. Actually, the field of application of this work is wider as it proposes to set up a possible theoretical framework for studying the overlapping extensions of classical mixed methods: the Dirichlet/Robin, Dirichlet/Neumann, Robin/Neumann and Robin/Robin DD methods. We observe that mixed DD methods inherit some properties of the Schwarz method while they keep the behavior of the classical mixed DD methods when the overlap tends to zero. As a main result, we show that the overlap makes the proposed methods more robust than disjoint mixed DD methods. The DD method we propose is geometric and algorithmic. It is geometric because the partition of the computational domain is performed before the meshing, and in accordance to the DD coupling. It is also algorithmic because the solution on each subdomain is obtained on separate processes and the exchange of information between the subdomains is carried out by a Master code. This strategy is very flexible as it requires almost no modification to the original numerical code. Therefore, only the Master code has to be adapted to the numerical codes and strategies used on each subdomain. We present a detailed description of the implementation of the DD methods in the numerical framework of finite elements. We present interpolation techniques for Dirichlet and Neumann data as well as conservation algorithms. Once the domain decomposition coupling and interpolation techniques are defined, we set up a Chimera method for the solution of the flow over objets in relative movements. Tensorial transformations are introduced to be able to express variables measures in one subdomain. Finally, the DD algorithm is applied to an implicit finite element code for the solution of the Navier-Stokes equations and also of the Reynolds Averaged Navier-Stokes equations together with a one-equation turbulence model.