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Peer Reviewed
See detailBuffer XDEM
Mainassara Chekaraou, Abdoul Wahid UL; Besseron, Xavier UL; Rousset, Alban UL et al

Scientific Conference (in press)

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See detailHigh-Performance Computing for the simulation of particles with the Discrete Element Method
Besseron, Xavier UL

Scientific Conference (2022, July 21)

In this talk, we will give an overview of the main techniques used for the parallelization of numerical simulations on High-Performance Computing platforms, and provide a particular focus on the Discrete ... [more ▼]

In this talk, we will give an overview of the main techniques used for the parallelization of numerical simulations on High-Performance Computing platforms, and provide a particular focus on the Discrete Element Method (DEM), a numerical method for the simulation of the motion of granular materials. We will cover the main parallelization paradigms and their implementations (shared memory with OpenMP and distributed memory with MPI), present the performance bottlenecks and introduce load-balancing techniques. [less ▲]

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Peer Reviewed
See detailParallel Multi-Physics Simulation of Biomass Furnace and Cloud-based Workflow for SMEs
Besseron, Xavier UL; Rusche, Henrik; Peters, Bernhard UL

in Practice and Experience in Advanced Research Computing (PEARC '22) (2022, July)

Biomass combustion is a well-established process to produce energy that offers a credible alternative to reduce the consumption of fossil fuel. To optimize the process of biomass combustion, numerical ... [more ▼]

Biomass combustion is a well-established process to produce energy that offers a credible alternative to reduce the consumption of fossil fuel. To optimize the process of biomass combustion, numerical simulation is a less expensive and time-effective approach than the experimental method. However, biomass combustion involves intricate physical phenomena that must be modeled (and validated) carefully, in the fuel bed and in the surrounding gas. With this level of complexity, these simulations require the use of High-Performance Computing (HPC) platforms and expertise, which are usually not affordable for manufacturing SMEs. In this work, we developed a parallel simulation tool for the simulation of biomass furnaces that relies on a parallel coupling between Computation Fluid Dynamics (CFD) and Discrete Element Method (DEM). This approach is computation-intensive but provides accurate and detailed results for biomass combustion with a moving fuel bed. Our implementation combines FOAM-extend (for the gas phase) parallelized with MPI, and XDEM (for the solid particles) parallelized with OpenMP, to take advantage of HPC hardware. We also carry out a thorough performance evaluation of our implementation using an industrial biomass furnace setup. Additionally, we present a fully automated workflow that handles all steps from the user input to the analysis of the results. Hundreds of parameters can be modified, including the furnace geometry and fuel settings. The workflow prepares the simulation input, delegates the computing-intensive simulation to an HPC platform, and collects the results. Our solution is integrated into the Digital Marketplace of the CloudiFacturing EU project and is directly available to SMEs via a Cloud portal. As a result, we provide a cutting-edge simulation of a biomass furnace running on HPC. With this tool, we demonstrate how HPC can benefit engineering and manufacturing SMEs, and empower them to compute and solve problems that cannot be tackled without. [less ▲]

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Peer Reviewed
See detailDevelopment of an HPC Multi-Physics Biomass Furnace Simulation and Integration in a Cloud-based Workflow
Besseron, Xavier UL; Henrik, Rusche; Peters, Bernhard UL

Scientific Conference (2022, June 09)

Biomass combustion offers a credible alternative to reduce the consumption of fossil fuels. To optimize the biomass combustion process and improve the design of biomass furnaces numerical simulation is a ... [more ▼]

Biomass combustion offers a credible alternative to reduce the consumption of fossil fuels. To optimize the biomass combustion process and improve the design of biomass furnaces numerical simulation is a less expensive and time-effective approach as opposed to the experimental method. However, the combustion in a biomass furnace involves intricate physical phenomena that must be modeled (and validated) carefully, in the fuel bed (with particle motion and shrinking, heat transfer, drying, pyrolysis, gasification) and in the surrounding gas (with turbulence, combustion, radiation). With this level of complexity, and to be conducted in a reasonable time, the simulation of industrial biomass furnaces requires the use of High-Performance Computing (HPC) platforms and expertise, which is usually not affordable for manufacturing SMEs. To address this issue, we developed a configurable digital twin of a biomass furnace running on HPC and we designed a cloudified easy-to-use end-to-end workflow. This fully automated workflow, from user input to results analysis, has been integrated into the digital marketplace of the CloudiFacturing EU project and is now directly available to SMEs via a Cloud portal. With this presentation, we want to offer a glance at the internal details and enabling technologies used in our parallel coupled application and scientific workflow. Our parallel simulation tool for biomass furnaces combines OpenFOAM (for the gas phase) parallelized with MPI and XDEM (for the solid wood particles) parallelized with OpenMP. The two libraries are coupled in parallel using an original approach based on the co-located partitioning strategy which has been tailored to minimize communications. As for the cloud workflow, it is based on an all-in-one Singularity image containing all the software, scripts, and data required to prepare the simulation input, execute the computation-intensive simulation, and analyze the results. Finally, we present the lessons learned from the development of this complex workflow and highlight the remaining challenges related to HPC multi-physics coupled simulations. [less ▲]

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See detailHEAT AND MASS TRANSFER BETWEEN XDEM & OPENFOAM USING PRECICE COUPLING LIBRARY
Adhav, Prasad UL; Besseron, Xavier UL; Estupinan Donoso, Alvaro Antonio UL et al

Scientific Conference (2022, June 09)

This work demonstrates the rapid development of a simulation environment to achieve Heat and Mass Transfer (HMT) between Discrete Element Methods (DEM) and Computa- tional Fluid Dynamics (CFD). The HMT ... [more ▼]

This work demonstrates the rapid development of a simulation environment to achieve Heat and Mass Transfer (HMT) between Discrete Element Methods (DEM) and Computa- tional Fluid Dynamics (CFD). The HMT coupling can be employed to simulate processes such as drying, pyrolysis, combustion, melting, solid-fluid reactions etc and have indus- trial applications such as biomass furnaces, boilers, heat exchangers, and flow through packed beds. This shows that diverse CFD features and solvers need to be coupled with DEM in order to achieve various applications mentioned above. The proposed DEM-CFD Eulerian-Lagrangian coupling for heat and mass transfer is achieved by employing the preCICE coupling library[1] on volumetric meshes. In our prototype, we use the eXtended Discrete Element Method (XDEM)[2] for handling DEM calculations and OpenFOAM for the CFD. The XDEM solver receives various CFD data fields such as fluid properties, and flow conditions exchanged through preCICE, which are used to set boundary conditions for particles. Various heat transfer and mass transfer laws have been implemented in XDEM to steer HMT source term computations. The heat and mass source terms computed by XDEM are transferred to CFD solver and added as source. These source terms represent particles in CFD. The generic coupling interface of preCICE, XDEM and its adapter allows to tackle a di- verse range of applications. We demonstrate the heat, mass & momentum coupling capa- bilities through various test cases and then compared with our legacy XDEM-OpenFOAM coupling and experimental results. [less ▲]

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Peer Reviewed
See detailRESIF 3.0: Toward a Flexible & Automated Management of User Software Environment on HPC facility
Varrette, Sébastien UL; Kieffer, Emmanuel UL; Pinel, Frederic UL et al

in ACM Practice and Experience in Advanced Research Computing (PEARC'21) (2021, July)

High Performance Computing (HPC) is increasingly identified as a strategic asset and enabler to accelerate the research and the business performed in all areas requiring intensive computing and large ... [more ▼]

High Performance Computing (HPC) is increasingly identified as a strategic asset and enabler to accelerate the research and the business performed in all areas requiring intensive computing and large-scale Big Data analytic capabilities. The efficient exploitation of heterogeneous computing resources featuring different processor architectures and generations, coupled with the eventual presence of GPU accelerators, remains a challenge. The University of Luxembourg operates since 2007 a large academic HPC facility which remains one of the reference implementation within the country and offers a cutting-edge research infrastructure to Luxembourg public research. The HPC support team invests a significant amount of time (i.e., several months of effort per year) in providing a software environment optimised for hundreds of users, but the complexity of HPC software was quickly outpacing the capabilities of classical software management tools. Since 2014, our scientific software stack is generated and deployed in an automated and consistent way through the RESIF framework, a wrapper on top of Easybuild and Lmod [5] meant to efficiently handle user software generation. A large code refactoring was performed in 2017 to better handle different software sets and roles across multiple clusters, all piloted through a dedicated control repository. With the advent in 2020 of a new supercomputer featuring a different CPU architecture, and to mitigate the identified limitations of the existing framework, we report in this state-of-practice article RESIF 3.0, the latest iteration of our scientific software management suit now relying on streamline Easybuild. It permitted to reduce by around 90% the number of custom configurations previously enforced by specific Slurm and MPI settings, while sustaining optimised builds coexisting for different dimensions of CPU and GPU architectures. The workflow for contributing back to the Easybuild community was also automated and a current work in progress aims at drastically decrease the building time of a complete software set generation. Overall, most design choices for our wrapper have been motivated by several years of experience in addressing in a flexible and convenient way the heterogeneous needs inherent to an academic environment aiming for research excellence. As the code base is available publicly, and as we wish to transparently report also the pitfalls and difficulties met, this tool may thus help other HPC centres to consolidate their own software management stack. [less ▲]

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See detailAWJC Nozzle simulation by 6-way coupling of DEM+CFD+FEM using preCICE coupling library
Adhav, Prasad UL; Besseron, Xavier UL; ROUSSET, Alban et al

Scientific Conference (2021, June 16)

The objective of this work is to study the particle-laden fluid-structure interaction within an Abrasive Water Jet Cutting Nozzle. Such coupling is needed to study the erosion phenomena caused by the ... [more ▼]

The objective of this work is to study the particle-laden fluid-structure interaction within an Abrasive Water Jet Cutting Nozzle. Such coupling is needed to study the erosion phenomena caused by the abrasive particles inside the nozzle. So far, the erosion in the nozzle was predicted only through the number of collisions, using only a simple DEM+CFD[1] coupling. To improve these predictions, we extend our model to a 6-way Eulerian-Lagrangian momentum coupling with DEM+CFD+FEM to account for deformations and vibrations in the nozzle. Our prototype uses the preCICE coupling library[2] to couple 3 numerical solvers: XDEM[3] (for the particle motion), OpenFOAM[4] (for the water jet), and CalculiX[5] (for the nozzle deformation). XDEM handles all the particle motions based on the fluid properties and flow conditions, and it calculates drag terms. In the fluid solver, particles are modeled as drag and are injected in the momentum equation as a source term. CalculiX uses the forces coming from the fluid solver and XDEM as boundary conditions to solve for the displacements. It is also used for computing the vibrations induced by particle impacts. . The preliminary 6-way DEM+CFD+FEM coupled simulation is able to capture the complex particle-laden multiphase fluid-structure interaction inside AWJC Nozzle. The erosion concentration zones are identified and are compared to DEM+CFD coupling[1]. The results obtained are planned to be used for predicting erosion intensity in addition to the concentration zones. In the future, we aim to compare the erosions predictions to experimental data in order to evaluate the suitability of our approach. The FEM module of the coupled simulation captures the vibration frequency induced by particles and compares it with the natural frequency of the nozzle. Thus opening up opportunities for further investigation and improvement of the Nozzle design. [less ▲]

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See detailOpenMP optimisation of the eXtended Discrete Element Method (XDEM)
Ojeda-May, Pedro; Eriksson, Jerry; Rousset, Alban UL et al

Report (2021)

The eXtended Discrete Element Method (XDEM) is an extension of the regular Discrete Element Method (DEM) which is a software for simulating the dynamics of granular material. XDEM extends the regular DEM ... [more ▼]

The eXtended Discrete Element Method (XDEM) is an extension of the regular Discrete Element Method (DEM) which is a software for simulating the dynamics of granular material. XDEM extends the regular DEM method by adding features where both micro and macroscopic observables can be computed simultaneously by coupling different time and length scales. In this sense XDEM belongs the category of multi-scale/multi-physics applications which can be used in realistic simulations. In this whitepaper, we detail the different optimisations done during the preparatory PRACE project to overcome known bottlenecks in the OpenMP implementation of XDEM. We analysed the Conversion, Dynamic, and the combined Dynamics-Conversion modules with Extrae/Paraver and Intel VTune profiling tools in order to find the most expensive functions. The proposed code modifications improved the performance of XDEM by ~17% for the computational expensive Dynamics-Conversion combined modules (with 48 cores, full node). Our analysis was performed in the Marenostrum 4 (MN4) PRACE infrastructure at Barcelona Supercomputing Center (BSC). [less ▲]

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See detailEvaluation of erosion inside AWJC Nozzle by 6-way coupling of DEM+CFD+FEM using preCICE
Adhav, Prasad UL; Besseron, Xavier UL; Rousset, Alban et al

Presentation (2021, February 23)

The objective of this work is to study the particle‐induced erosion within a nozzle for abrasive cutting. So far, the erosion in the nozzle was predicted only through the number of collisions, using only ... [more ▼]

The objective of this work is to study the particle‐induced erosion within a nozzle for abrasive cutting. So far, the erosion in the nozzle was predicted only through the number of collisions, using only a simple DEM+CFD coupling. To improve these predictions, we extend our model to a 6‐way momentum coupling with DEM+CFD+FEM to account for deformations and vibrations in the nozzle. Our prototype uses preCICE to couple 3 numerical solvers: XDEM (for the particle motion), OpenFOAM (for the water jet), and CalculiX (for the nozzle deformation). The OpenFOAM adapter has been adapted to add particles drag, which is modeled as semi‐implicit porosity, implicit and explicit drag terms injected to OpenFOAM solver through fvOptions. This 6‐way coupling between DEM+CFD+FEM brings the simulation of the particle‐laden multiphase flow inside the abrasive cutting nozzle close to the real‐life conditions. Thus opening up opportunities for further investigation and improvement of the Nozzle design. [less ▲]

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Peer Reviewed
See detailEulerian-Lagrangian momentum coupling between XDEM and OpenFOAM using preCICE
Besseron, Xavier UL; Rousset, Alban UL; Peyraut, Alice et al

in 14th WCCM & ECCOMAS Congress 2020 (2021, January)

Eulerian-Lagrangian couplings consider problems with a discrete phase as a particulate material that is in contact with a fluid phase. These applications are as diverse as engineering, additive ... [more ▼]

Eulerian-Lagrangian couplings consider problems with a discrete phase as a particulate material that is in contact with a fluid phase. These applications are as diverse as engineering, additive manufacturing, biomass conversion, thermal processing or pharmaceutical industry, among many others. A typical approach for this type of simulations is the coupling between Computation Fluid Dynamics (CFD) and Discrete Element Method (DEM), which is challenging in many ways. Such CFD--DEM couplings are usually implemented using an ad-hoc coupling layer, specific to the both DEM and CFD software, which considerably reduces the flexibility and applicability of the proposed implementation. In this work, we present the coupling of eXtended Discrete Element Method (XDEM), with the CFD library OpenFOAM, using the preCICE coupling library~\cite{preCICE} on volumetric meshes. Such momentum coupling requires the CFD side to account for the change of porosity due to the particulate phase and the particle momentum, while the particles of the DEM will be affected by the buoyancy and drag force of the fluid. While preCICE significantly simplifies the coupling between standalone libraries, each solver and, its respective adapter, have to be made aware of the new data involved in the physic model. For that, a new adapter has been implemented for XDEM and the existing adapter for OpenFOAM has been extended to include the additional data field exchange required for the momentum coupling, e.g porosity, particle momentum, fluid velocity and density. Our solution is tested and validated using simple benchmarks and advanced testcases such as a dam break, and shows consistent results. [less ▲]

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Peer Reviewed
See detailProcess analysis in thermal process engineering with high-performance computing using the example of grate firing
Peters, Bernhard UL; Rousset, Alban UL; Besseron, Xavier UL et al

in Scherer, Viktor; Fricker, Neil; Reis, Albino (Eds.) Proceedings of the 12th European Conference on Industrial Furnaces and Boilers (2020, November)

Biomass as a renewable energy source continues to grow in popularity to reduce fossil fuel consumption for environmental and economic benefits. In the present contribution, the combustion chamber of a 16 ... [more ▼]

Biomass as a renewable energy source continues to grow in popularity to reduce fossil fuel consumption for environmental and economic benefits. In the present contribution, the combustion chamber of a 16 MW geothermal steam super-heater, which is part of the Enel Green Power "Cornia 2" power plant, is being investigated with high-performance computing methods. For this purpose, the extended discrete element method (XDEM) developed at the University of Luxembourg is used in a high-performance computing environment, which includes both the moving wooden bed and the combustion chamber above it. The XDEM simulation platform is based on a hybrid four-way coupling between the Discrete Element Method (DEM) and Computational Fluid Dynamics (CFD). In this approach, particles are treated as discrete elements that are coupled by heat, mass, and momentum transfer to the surrounding gas as a continuous phase. For individual wood particles, besides the equations of motion, the differential conservation equations for mass, heat, and momentum are solved, which describe the thermodynamic state during thermal conversion. The consistency of the numerical results with the actual system performance is discussed in this paper to determine the potentials and limitations of the approach. [less ▲]

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See detailHPC Multi-physics Biomass Furnace simulations as a Service
Besseron, Xavier UL; Rusche, Henrik; Peters, Bernhard UL et al

Scientific Conference (2020, November)

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Peer Reviewed
See detailLowering the obstacles for SMEs to adopt multi-physics biomass furnace simulations by providing a cloud based solution
Rusche, Henrik; Peters, Bernhard UL; Besseron, Xavier UL et al

Scientific Conference (2020, October 14)

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Peer Reviewed
See detailNumerical Analysis of Interaction between a Reacting Fluid and a Moving Bed with Spatially and Temporally Fluctuating Porosity
Rousset, Alban UL; Mainassara Chekaraou, Abdoul Wahid UL; Besseron, Xavier UL et al

Scientific Conference (2020, August 31)

The purpose of this study is to propose a numerical approach that combines low computational costs through the use of high computing efficiency, allowing the realistic use of the design with a sufficient ... [more ▼]

The purpose of this study is to propose a numerical approach that combines low computational costs through the use of high computing efficiency, allowing the realistic use of the design with a sufficient result's accuracy for industrial applications to investigate biomass combustion in a large-scale reciprocating grate. In the present contribution, a Biomass combustion chamber of a 16 MW geothermal steam super-heater, which is part of the Enel Green Power "Cornia 2" power plant,is being investigated with high-performance computing methods. For this purpose, the extended discrete element method (XDEM) developed at the University of Luxembourg is used in an HPC environment, which includes both the moving wooden bed and the combustion chamber above it. The XDEM simulation platform is based on a hybrid four-way coupling between the Discrete Element Method (DEM) and Computational Fluid Dynamics (CFD). In this approach, particles are treated as discrete elements that are coupled by heat, mass, and momentum transfer to the surrounding gas as a continuous phase. For individual wood particles, besides the equations of motion, the differential conservation equations for mass, heat, and momentum are solved, which describe the thermodynamic state during thermal conversion. The grate system has three different moving sections to ensure good mixing of the biomass parts and appropriate residence time. The primary air enters from below the grate and is split into four different zones. Furthermore, a secondary air is injected at high velocity straight over the fuel bed through nozzles. A Flue Gas Recirculation is present and partly injected through two jets along the vertical channel and partly from below the grate. The numerical 3D model presented is based on a multi-phase approach. The biomass particles are taken into consideration via the XDEM Method, while the gaseous phase is described by CFD with OpenFOAM. Thus, the combustion of the particles on the moving beds in the furnace is processed by XDEM through conduction, radiation and conversion along with the interaction with the surrounding gas phase accounted for by CFD. The coupling of CFD-XDEM as an Euler-Lagrange model is used. The fluid phase is a continuous phase handled with an Eulerian approach and each particle is tracked with a Lagrangian approach. Energy, mass and momentum conservation is applied for every single particle and the interaction of particles with each other in the bed and with the surrounding gas phase are taken into account. An individual particle can have a solid, liquid, gas or inert material phases (immobile species) at the same time. The different phases can undergo a series of conversion through various reactions that can be homogeneous, heterogeneous or intrinsic (drying, pyrolysis, gasification and oxidation). Our first results are consistent with actual data obtained from the sampling of the residual solid in the industrial plant. Our model is also able to predict gas flux behaviour inside the furnace, particularly the flue gas recirculation on the combustion process injection. [less ▲]

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See detailParallel coupling strategy for multi-physics applications in eXtended Discrete Element Method
Besseron, Xavier UL; Rousset, Alban UL; Mainassara Chekaraou, Abdoul Wahid UL et al

Scientific Conference (2020, June 18)

Multi-physics problems containing discrete particles interacting with fluid phases are widely used industry for example in biomass combustion on a moving grate, particle sedimentation, iron production ... [more ▼]

Multi-physics problems containing discrete particles interacting with fluid phases are widely used industry for example in biomass combustion on a moving grate, particle sedimentation, iron production within a blast furnace, and selective laser melting for additive manufacturing. The eXtended Discrete Element Method (XDEM) uses a coupled Eulerian-Lagrangian approach to simulate these complex phenomena, and relies on the Discrete Element Method (DEM) to model the particle phase and Computational Fluid Dynamics (CFD) for the fluid phases, solved respectively with XDEM and OpenFOAM. However, such simulations are very computationally intensive. Additionally, because the DEM particles move within the CFD phases, a 3D volume coupling is required, hence it represents an important amount of data to be exchanged. This volume of communication can have a considerable impact on the performance of the parallel execution. To address this issue, XDEM has proposed a coupling strategy relying on a co-located partitioning. This approach coordinates the domain decomposition of the two independent solvers, XDEM and OpenFOAM, to impose some co-location constraints and reduce the overhead due to the coupling data exchange. This strategy for the parallel coupling of CFD-DEM has been evaluated to perform large scale simulations of debris within a dam break flow. [less ▲]

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Peer Reviewed
See detailPredicting near-optimal skin distance in Verlet buffer approach for Discrete Element Method
Mainassara Chekaraou, Abdoul Wahid UL; Besseron, Xavier UL; Rousset, Alban UL et al

in 10th IEEE Workshop on Parallel / Distributed Combinatorics and Optimization (2020, June)

The Verlet list method is a well-known bookkeeping technique of the interaction list used both in Molecular Dynamic (MD) and Discrete Element Method (DEM). The Verlet buffer technique is an enhancement of ... [more ▼]

The Verlet list method is a well-known bookkeeping technique of the interaction list used both in Molecular Dynamic (MD) and Discrete Element Method (DEM). The Verlet buffer technique is an enhancement of the Verlet list that consists of extending the interaction radius of each particle by an extra margin to take into account more particles in the interaction list. The extra margin is based on the local flow regime of each particle to account for the different flow regimes that can coexist in the domain. However, the choice of the near-optimal extra margin (which ensures the best performance) for each particle and the related parameters remains unexplored in DEM unlike in MD. In this study, we demonstrate that the near-optimal extra margin can fairly be characterized by four parameters that describe each particle local flow regime: the particle velocity, the ratio of the containing cell size to particle size, the containing cell solid fraction, and the total number of particles in the system. For this purpose, we model the near-optimal extra margin as a function of these parameters using a quadratic polynomial function. We use the DAKOTA SOFTWARE to carry out the Design and Analysis of Computer Experiments (DACE) and the sampling of the parameters for the simulations. For a given instance of the set of parameters, a global optimization method is considered to find the near-optimal extra margin. The latter is required for the construction of the quadratic polynomial model. The numerous simulations generated by the sampling of the parameter were performed on a High-Performance Computing (HPC) environment granting parallel and concurrent executions. This work provides a better understanding of the Verlet buffer method in DEM simulations by analyzing its performances and behavior in various configurations. The near-optimal extra margin can reasonably be predicted by two out of the four chosen parameters using the quadratic polynomial model. This model has been integrated into XDEM in order to automatically choose the extra margin without any input from the user. Evaluations on real industrial-level test cases show up to a 26% reduction of the execution time. [less ▲]

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See detail6-way coupling of DEM+CFD+FEM with preCICE
Besseron, Xavier UL; Rousset, Alban UL; Peyraut, Alice et al

Presentation (2020, February)

In this work, we present our preliminary results on the 6-way coupling of 3 numerical solvers: XDEM for the Discrete Element Method (DEM), OpenFOAM for Computation Fluid Dynamics (CFD), and deal.II for ... [more ▼]

In this work, we present our preliminary results on the 6-way coupling of 3 numerical solvers: XDEM for the Discrete Element Method (DEM), OpenFOAM for Computation Fluid Dynamics (CFD), and deal.II for Finite Element Method (FEM). We relied on the existing preCICE adapters for OpenFOAM and deal.II and we have implemented a new preCICE adapter for the eXtended Discrete Element Method (XDEM), an innovative DEM software developed at the University of Luxembourg. The XDEM adapter permits coupling of the particulate phase of DEM with CFD and FEM: - DEM+FEM is a surface coupling that performs the exchange of surface forces and displacement between the particles and a deformable solid; - DEM+CFD is a volume coupling that performs the exchange of porosity, momentum, drag force and buoyancy between the particles and the fluid. Put together with the pre-existing CFD+FEM coupling, we obtain a 6-way coupled multi-physics solver for particles, fluid and deformable solids. We have tested and evaluated our multi-physics solver on the tutorial case “Cylinder with a flap” derived from the benchmarking case of Turek and Hron, that we extended to include a particulate phase solved by XDEM. [less ▲]

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See detailVerlet buffer for (X)DEM
Mainassara Chekaraou, Abdoul Wahid UL; Rousset, Alban UL; Besseron, Xavier UL et al

Scientific Conference (2019, July 26)

The Extended Discrete Element Method (XDEM) is a novel and innovative numerical simulation technique that extends the dynamics of granular materials or particles as described through the classical ... [more ▼]

The Extended Discrete Element Method (XDEM) is a novel and innovative numerical simulation technique that extends the dynamics of granular materials or particles as described through the classical discrete element method (DEM) by additional properties such as the thermodynamic state, stress/strain for each particle. Such DEM simulations used by industries to set up their experimental processes are complex and heavy in computation time. Those simulations perform at each time step a collision detection to generate a list of interacting particles that is one of the most expensive computation parts of a DEM simulation. The Verlet buffer method, which was first introduced in Molecular Dynamic (MD) (and is also used in DEM) allows to keep the interaction list for many time step by extending each particle neighborhood by a certain extension range, and thus broadening the interaction list. The method relies mainly on the stability of the DEM, which ensures that no particles move erratically or unpredictably from one time step to the next: this is called temporal coherency. In the classical and current approach, all the particles have their neighborhood extended by the same value which leads to suboptimal performances in simulations where different flow regimes coexist. Additionally, and unlike in MD (which remains very different from DEM on several aspects), there is no comprehensive study analyzing the different parameters that affect the performance of the Verlet buffer method in DEM. In this work, we apply a dynamic neighbor list update method that depends on the particle's individual displacement, and an extension range specific to each particle and based on their local flow regime for the generation of the neighbor list. The update of the interaction list is analyzed throughout the simulation based on the displacement of the particle allowing a flexible update according to the flow regime conditions. We evaluate the influence of the Verlet extension range on the performance of the execution time through different test cases and we empirically analyze and define the extension range value giving the minimum of the global simulation time. [less ▲]

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See detailHigh Performance Parallel Coupling of OpenFOAM+XDEM
Besseron, Xavier UL; Pozzetti, Gabriele; Rousset, Alban UL et al

Presentation (2019, June 21)

Detailed reference viewed: 276 (28 UL)