References of "Besseron, Xavier 50000761"
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See detailOn the performance of an overlapping-domain parallelization strategy for Eulerian-Lagrangian Multiphysics software
Pozzetti, Gabriele UL; Besseron, Xavier UL; Rousset, Alban UL et al

in AIP Conference Proceedings ICNAAM 2017 (in press)

In this work, a strategy for the parallelization of a two-way CFD-DEM coupling is investigated. It consists on adopting balanced overlapping partitions for the CFD and the DEM domains, that aims to reduce ... [more ▼]

In this work, a strategy for the parallelization of a two-way CFD-DEM coupling is investigated. It consists on adopting balanced overlapping partitions for the CFD and the DEM domains, that aims to reduce the memory consumption and inter-process communication between CFD and DEM. Two benchmarks are proposed to assess the consistency and scalability of this approach, coupled execution on 252 cores shows that less than 1\% of time is used to perform inter-physics data exchange. [less ▲]

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See detailComparing Broad-Phase Interaction Detection Algorithms for Multiphysics DEM Applications
Rousset, Alban UL; Mainassara Chekaraou, Abdoul Wahid UL; Liao, Yu-Chung UL et al

in AIP Conference Proceedings ICNAAM 2017 (2017, September)

Collision detection is an ongoing source of research and optimization in many fields including video-games and numerical simulations [6, 7, 8]. The goal of collision detection is to report a geometric ... [more ▼]

Collision detection is an ongoing source of research and optimization in many fields including video-games and numerical simulations [6, 7, 8]. The goal of collision detection is to report a geometric contact when it is about to occur or has actually occurred. Unfortunately, detailed and exact collision detection for large amounts of objects represent an immense amount of computations, naively n 2 operation with n being the number of objects [9]. To avoid and reduce these expensive computations, the collision detection is decomposed in two phases as it shown on Figure 1: the Broad-Phase and the Narrow-Phase. In this paper, we focus on Broad-Phase algorithm in a large dynamic three-dimensional environment. We studied two kinds of Broad-Phase algorithms: spatial partitioning and spatial sorting. Spatial partitioning techniques operate by dividing space into a number of regions that can be quickly tested against each object. Two types of spatial partitioning will be considered: grids and trees. The grid-based algorithms consist of a spatial partitioning processing by dividing space into regions and testing if objects overlap the same region of space. And this reduces the number of pairwise to test. The tree-based algorithms use a tree structure where each node spans a particular space area. This reduces the pairwise checking cost because only tree leaves are checked. The spatial sorting based algorithm consists of a sorted spatial ordering of objects. Axis-Aligned Bounding Boxes (AABBs) are projected onto x, y and z axes and put into sorted lists. By sorting projection onto axes, two objects collide if and only if they collide on the three axes. This axis sorting reduces the number of pairwise to tested by reducing the number of tests to perform to only pairs which collide on at least one axis. For this study, ten different Broad-Phase collision detection algorithms or framework have been considered. The Bullet [6], CGAL [10, 11] frameworks have been used. Concerning the implemented algorithms most of them come from papers or given implementation. [less ▲]

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See detailParallelizing XDEM: Load-balancing policies and efficiency, a study
Rousset, Alban UL; Besseron, Xavier UL; Peters, Bernhard UL

Scientific Conference (2017, September)

In XDEM, the simulation domain is geometrically decomposed in regular fixed-size cells that are used to distribute the workload between the processes. The role of the partitioning algorithm is to ... [more ▼]

In XDEM, the simulation domain is geometrically decomposed in regular fixed-size cells that are used to distribute the workload between the processes. The role of the partitioning algorithm is to distribute the cells among all the processes in order to balance the workload. To accomplish this task, the partitioning algorithm relies on a computing/communication cost that has been estimated for each cell. A proper estimation of these costs is fundamental to obtain pertinent results during this phase. The study in the work is twofold. First, we integrate five partitioning algorithms (ORB, RCB, RIB, kway and PhG) in the XDEM framework [1]. Most of these algorithms are implemented within the Zoltan library [2], a parallel framework for partitioning and ordering problems. Secondly, we propose different policies to estimate the computing cost and communication cost of the different cells composing the simulation domain. Then, we present an experimental evaluation and a performance comparison of these partitioning algorithms and cost-estimation policies on a large scale parallel execution of XDEM running on the HPC platform of the University of Luxembourg. Finally, after explaining the pros and cons of each partitioning algorithms and cost-estimation policies, we discuss on the best choices to adopt depending on the simulation case. [less ▲]

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See detailModeling of the biomass combustion on a forward acting grate using XDEM
Mahmoudi, Amir Houshang UL; Besseron, Xavier UL; Hoffmann, F. et al

in Chemical Engineering Science (2016), 142

The grate firing system is one of the most common ways for the combustion of biomass because it is able to burn a broad range of fuels with only little or even no requirement for fuel preparation. In ... [more ▼]

The grate firing system is one of the most common ways for the combustion of biomass because it is able to burn a broad range of fuels with only little or even no requirement for fuel preparation. In order to improve the fuel combustion efficiency, it is important to understand the details of the thermochemical process in such furnaces. However, the process is very complex due to many involved physical and chemical phenomena such as drying, pyrolysis, char combustion, gas phase reaction, two phase flow and many more. The main objective of this work is to study precisely the involved processes in biomass combustion on a forward acting grate and provide a detailed insight into the local and global conversion phenomena. For this purpose, XDEM as an Euler-Lagrange model is used, in which the fluid phase is a continuous phase and each particle is tracked with a Lagrangian approach. The model has been compared with experimental data. Very good agreements between simulation and measurement have been achieved, proving the ability of the model to predict the biomass combustion under study on the grate. © 2015 Elsevier Ltd. [less ▲]

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See detailHPC or the Cloud: a cost study over an XDEM Simulation
Emeras, Joseph; Besseron, Xavier UL; Varrette, Sébastien UL et al

in Proc. of the 7th International Supercomputing Conference in Mexico (ISUM 2016) (2016)

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See detailNumerical study of the influence of particle size and packing on pyrolysis products using XDEM
Mahmoudi, Amir Houshang UL; Hoffmann, F.; Peters, Bernhard UL et al

in International Communications in Heat & Mass Transfer (2016), 71

Conversion of biomass as a renewable source of energy is one of the most challenging topics in industry and academy. Numerical models may help designers to understand better the details of the involved ... [more ▼]

Conversion of biomass as a renewable source of energy is one of the most challenging topics in industry and academy. Numerical models may help designers to understand better the details of the involved processes within the reactor, to improve process control and to increase the efficiency of the boilers. In this work, XDEM as an Euler-Lagrange model is used to predict the heat-up, drying and pyrolysis of biomass in a packed bed of spherical biomass particles. The fluid flow through the void space of a packed bed (which is formed by solid particles) is modeled as three-dimensional flow through a porous media using a continuous approach. The solid phase forming the packed bed is represented by individual, discrete particles which are described by a Lagrangian approach. On the particle level, distributions of temperature and species within a single particle are accounted for by a system of one-dimensional and transient conservation equations. The model is compared to four sets of experimental data from independent research groups. Good agreements with all experimental data are achieved, proving reliability of the used numerical methodology. The proposed model is used to investigate the impact of particle size in combination with particle packing on the char production. For this purpose, three setups of packed beds differing in particle size and packing mode are studied under the same process conditions. The predicted results show that arranging the packed bed in layers of small and large particles may increase the final average char yield for the entire bed by 46 %. © 2015 Elsevier B.V. [less ▲]

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See detailPerformance Evaluation of the XDEM framework on the OpenStack Cloud Computing Middleware
Besseron, Xavier UL; Plugaru, Valentin UL; Mahmoudi, Amir Houshang UL et al

in Proceedings of the Fourth International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering (2015, February)

As Cloud Computing services become ever more prominent, it appears necessary to assess the efficiency of these solutions. This paper presents a performance evaluation of the OpenStack Cloud Computing ... [more ▼]

As Cloud Computing services become ever more prominent, it appears necessary to assess the efficiency of these solutions. This paper presents a performance evaluation of the OpenStack Cloud Computing middleware using our XDEM application simulating the pyrolysis of biomass as a benchmark. We propose a systematic study based on a fully automated benchmarking framework to evaluate 3 different configurations: Native (i.e. no virtualization), OpenStack with KVM and XEN hypervisors. Our approach features the following advantages: real user application, the fair comparison using the same hardware, the large scale distributed execution, while fully automated and reproducible. Experiments has been run on two different clusters, using up to 432 cores. Results show a moderate overhead for sequential execution and a significant penalty for distributed execution under the Cloud middleware. The overhead on multiple nodes is between 10% and 30% for OpenStack/KVM and 30% and 60% for OpenStack/XEN. [less ▲]

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See detailA discrete/continuous numerical approach to multi-physics
Peters, Bernhard UL; Besseron, Xavier UL; Estupinan Donoso, Alvaro Antonio UL et al

in IFAC-PapersOnLine (2015), 28(1), 645-650

A variety of technical applications are not only the physics of a single domain, but include several physical phenomena, and therefore are referred to as multi-physics. As long as the phenomena being ... [more ▼]

A variety of technical applications are not only the physics of a single domain, but include several physical phenomena, and therefore are referred to as multi-physics. As long as the phenomena being taken into account is either continuous or discrete i.e. Euler or Lagrangian a homogeneous solution concept can be employed. However, numerous challenges in engineering include continuous and discrete phase simultaneously, and therefore cannot be solved only by continuous or discrete approaches. Problems include both a continuous and a discrete phase are important in applications of the pharmaceutical Industry e.g. drug production, agriculture and food processing industry, mining, construction and Agricultural machinery, metal production, power generation and systems biology. The Extended Discrete Element Method (XDEM) is a novel technique, which provides a significant advance for the coupled discrete and continuous numerical simulation concepts. It expands the dynamics of particles as described by the classical discrete element method (DEM) by a thermodynamic state or stress/strain coupled as fluid flow or structures for each particle in a continuum phase. XDEM additionally estimates properties such as the interior temperature and/or species distribution. These predictive capabilities are extended to fluid flow through an interaction by heat, mass and momentum transfer important for process engineering. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. [less ▲]

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See detailAssessing Heat Transfer Through Walls Of Packed Bed Reactors By An Innovative Particle-Resolved Approach
Peters, Bernhard UL; Singhal, A.; Besseron, Xavier UL et al

in 18th IFRF Member's Conference (2015)

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See detailParaMASK: a Multi-Agent System for the Efficient and Dynamic Adaptation of HPC Workloads
Guzek, Mateusz UL; Besseron, Xavier UL; Varrette, Sébastien UL et al

in 14th IEEE International Symposium on Signal Processing and Information Technology (ISSPIT 2014) (2014, December)

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See detailHPC Performance and Energy-Efficiency of the OpenStack Cloud Middleware
Varrette, Sébastien UL; Plugaru, Valentin UL; Guzek, Mateusz UL et al

in Proc. of the 43rd Intl. Conf. on Parallel Processing (ICPP-2014), Heterogeneous and Unconventional Cluster Architectures and Applications Workshop (HUCAA'14) (2014, September)

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See detailAn Integral Approach to Multi-physics Application for Packed Bed Reactors
Peters, Bernhard UL; Besseron, Xavier UL; Estupinan, A. et al

in 24th European Symposium on Computer Aided Process Engineering, ESCAPE 24 (2014)

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See detailThe extended discrete element method (XDEM) applied to drying of a packed bed
Peters, Bernhard UL; Besseron, Xavier UL; Estupinan Donoso, Alvaro Antonio UL et al

in Industrial Combustion (2014), 14

A vast number of engineering applications involve physics not solely of a single domain but of several physical phenomena, and therefore are referred to as multi-physical. As long as the phenomena ... [more ▼]

A vast number of engineering applications involve physics not solely of a single domain but of several physical phenomena, and therefore are referred to as multi-physical. As long as the phenomena considered are to be treated by either a continuous (i.e. Eulerian) or discrete (i.e. Lagrangian) approach, numerical solution methods may be employed to solve the problem. However, numerous challenges in engineering exist and evolve; those include modelling a continuous and discrete phase simultaneously, which cannot be solved accurately by continuous or discrete approaches only. Problems that involve both a continuous and a discrete phase are important in applications as diverse as the pharmaceutical industry, the food processing industry, mining, construction, agricultural machinery, metals manufacturing, energy production and systems biology. A novel technique referred to as Extended Discrete Element Method (XDEM) has been developed that offers a significant advancement for coupled discrete and continuous numerical simulation concepts. XDEM extends the dynamics of granular materials or particles as described through the classical discrete element method (DEM) to include additional properties such as the thermodynamic state or stress/strain for each particle coupled to a continuous phase such as a fluid flow or a solid structure. Contrary to a continuum mechanics concept, XDEM aims at resolving the particulate phase through the various processes attached to particles. While DEM predicts the spatial-temporal position and orientation for each particle, XDEM additionally estimates properties such as the internal temperature and/or species distribution during drying, pyrolysis or combustion of solid fuel material such as biomass in a packed bed. These predictive capabilities are further extended by an interaction with fluid flow by heat, mass and momentum transfer and the impact of particles on structures. © International Flame Research Foundation, 2014. [less ▲]

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See detailScale-Resolved Prediction of Pyrolysis in a Packed Bed by the Extended Discrete Element Method (XDEM)
Peters, Bernhard UL; Besseron, Xavier UL; Estupinan, A. et al

in The Ninth International Conference on Engineering Computational Technology (2014)

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See detailHPC Performance and Energy-Efficiency of Xen, KVM and VMware Hypervisors
Varrette, Sébastien UL; Guzek, Mateusz UL; Plugaru, Valentin UL et al

in Proc. of the 25th Symposium on Computer Architecture and High Performance Computing (SBAC-PAD 2013) (2013, October)

With a growing concern on the considerable energy consumed by HPC platforms and data centers, research efforts are targeting green approaches with higher energy efficiency. In particular, virtualization ... [more ▼]

With a growing concern on the considerable energy consumed by HPC platforms and data centers, research efforts are targeting green approaches with higher energy efficiency. In particular, virtualization is emerging as the prominent approach to mutualize the energy consumed by a single server running multiple VMs instances. Even today, it remains unclear whether the overhead induced by virtualization and the corresponding hypervisor middleware suits an environment as high-demanding as an HPC platform. In this paper, we analyze from an HPC perspective the three most widespread virtualization frameworks, namely Xen, KVM, and VMware ESXi and compare them with a baseline environment running in native mode. We performed our experiments on the Grid’5000 platform by measuring the results of the reference HPL benchmark. Power measures were also performed in parallel to quantify the potential energy efficiency of the virtualized environments. In general, our study offers novel incentives toward in-house HPC platforms running without any virtualized frameworks. [less ▲]

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See detailUnified Design for Parallel Execution of Coupled Simulations using the Discrete Particle Method
Besseron, Xavier UL; Hoffmann, Florian UL; Michael, Mark UL et al

in Proceedings of the Third International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering (2013)

This paper presents the enhanced design of the Discrete Particle Method (DPM), a simulation tool which provides high quality and fast simulations to solve a broad range industrial processes involving ... [more ▼]

This paper presents the enhanced design of the Discrete Particle Method (DPM), a simulation tool which provides high quality and fast simulations to solve a broad range industrial processes involving granular materials. It enables to resolve mechanical and thermodynamics problems through different simulation modules (motions, chemical conversion). This new design allows to transparently couple the simulation modules in parallel execution. It relies on a unified interface and timebase of the simulation modules and a flexible decomposition in cells of the simulation space. Experimental results study the behavior of the Orthogonal Recursive Bisection (ORB) partitioning algorithm. A good scalability is achieved as the parallel execution on a distributed platform provides a 17-times speedup using 64 processes. [less ▲]

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See detailUsing Data-flow analysis in MAS for power-aware HPC runs
Varrette, Sébastien UL; Danoy, Grégoire UL; Guzek, Mateusz UL et al

in Proc. of the IEEE Intl. Conf. on High Performance Computing and Simulation (HPCS'13) (2013)

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See detailEnhanced Thermal Process Engineering by the Extended Discrete Element Method (XDEM)
Peters, Bernhard UL; Besseron, Xavier UL; Estupinan Donoso, Alvaro Antonio UL et al

in Universal Journal of Engineering Science (2013), 1

A vast number of engineering applications <br />include a continuous and discrete phase simultaneously, <br />and therefore, cannot be solved accurately by continu- <br />ous or discrete approaches only ... [more ▼]

A vast number of engineering applications <br />include a continuous and discrete phase simultaneously, <br />and therefore, cannot be solved accurately by continu- <br />ous or discrete approaches only. Problems that involve <br />both a continuous and a discrete phase are important <br />in applications as diverse as pharmaceutical industry <br />e.g. drug production, agriculture food and process- <br />ing industry, mining, construction and agricultural <br />machinery, metals manufacturing, energy production <br />and systems biology. A novel technique referred to as <br />Extended Discrete Element Method (XDEM) is devel- <br />oped, that o ers a signi cant advancement for coupled <br />discrete and continuous numerical simulation concepts. <br />The Extended Discrete Element Method extends the <br />dynamics of granular materials or particles as described <br />through the classical discrete element method (DEM) to <br />additional properties such as the thermodynamic state <br />or stress/strain for each particle coupled to a continuum <br />phase such as <br />uid <br />ow or solid structures. Contrary <br />to a continuum mechanics concept, XDEM aims at <br />resolving the particulate phase through the various <br />processes attached to particles. While DEM predicts <br />the spacial-temporal position and orientation for each <br />particle, XDEM additionally estimates properties such <br />as the internal temperature and/or species distribution. <br />These predictive capabilities are further extended by an <br />interaction to <br />uid <br />ow by heat, mass and momentum <br />transfer and impact of particles on structures. [less ▲]

Detailed reference viewed: 142 (25 UL)