References of "Besseron, Xavier 50000761"
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See detailRapidRMSD: Rapid determination of RMSDs corresponding to motions of flexible molecules
Neveu, Emilie; Popov, Petr; Hoffmann, Alexandre et al

in Bioinformatics (2018)

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See detailA Parallel Multiscale DEM-VOF Method For Large-Scale Simulations Of Three-Phase Flows
Pozzetti, Gabriele UL; Besseron, Xavier UL; Rousset, Alban UL et al

in Proceedings of ECCM-ECFD 2018 (2018)

A parallel dual-grid multiscale DEM-VOF coupling is here investigated. Dual- grid multiscale couplings have been recently used to address different engineering problems involving the interaction between ... [more ▼]

A parallel dual-grid multiscale DEM-VOF coupling is here investigated. Dual- grid multiscale couplings have been recently used to address different engineering problems involving the interaction between granular phases and complex fluid flows. Nevertheless, previous studies did not focus on the parallel performance of such a coupling and were, therefore, limited to relatively small applications. In this contribution, we propose an insight into the performance of the dual-grid multiscale DEM-VOF method for three- phase flows when operated in parallel. In particular,we focus on a famous benchmark case for three-phase flows and assess the influence of the partitioning algorithm on the scalability of the dual-grid algorithm. [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 detailXDEM: from HPC to the Cloud
Besseron, Xavier UL

Scientific Conference (2017, January)

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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 and 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 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 detailUL HPC in practice: why, what, how, where to look
Besseron, Xavier UL

Presentation (2015, June 25)

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See detailXDEM: eXtended Discrete Element Method
Besseron, Xavier UL; Peters, Bernhard UL

Presentation (2015, June 16)

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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 detailXDEM Research on UL HPC platform
Besseron, Xavier UL

Presentation (2014, May 07)

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See detailATIS: Automated Testing of Installed Software. Or so far, How to validate MPI stacks of an HPC cluster?
Besseron, Xavier UL

Presentation (2014, February 01)

Automatic Testing of Installed Software is a testing framework to validate the various flavors of software installed on an HPC site. It is composed of a set of unit tests, a runtime and a result-gathering ... [more ▼]

Automatic Testing of Installed Software is a testing framework to validate the various flavors of software installed on an HPC site. It is composed of a set of unit tests, a runtime and a result-gathering dashboard. These tests are user-oriented as they assess the basic features that a general user expect to work on an HPC platform. Currently, it only focuses on generic MPI functionality as it is one complex and critical component of an HPC platform, but it will be extended to compilers, libraries and performance validation and regression in the future. HPC centers tend to provide a wide choice a software. Different users requires different software, but also different versions of the same software. Combined with the different compilers, MPI stacks, library dependencies, there is an explosion of software flavors installed on an HPC site. Tools already exist to help managing this large variety of software. Users can choose their software through the software list using the 'module' system. Administrators can perform automatic compilation and installation of software using EasyBuild. Additionally, software also require some customizations on some HPC sites. Thus, software flavors need to be validated after installation to check they're working as expected by the users. We developed and provide a set of unit tests together with a runtime and result-gathering framework to perform a such Automatic Testing of Installed Software. These tests take the side of the users in order to test any basic feature that a general user expect to work on an HPC platform. So far, the proposed tests only focus on generic MPI functionality as it is one complex and critical component of an HPC platform. The unit tests include, for example, compilation with mpicc and distributed execution with mpiexec. It has been applied successfully on the HPC platforms of the University of Luxembourg to assess builds of OpenMPI, MPICH, MVAPICH2 and IntelMPI generated with EasyBuild. In the future, we consider extending our unit tests to validate more components like compilers, libraries, toolchains and even applications. Another future direction is to consider performance validation and regression. [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 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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