References of "Besseron, Xavier 50000761"
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See detailDetermination of Kinetic Parameters for Heterogeneous Reaction System Employing Discrete Element Methods under HPC Platforms
Estupinan Donoso, Alvaro Antonio UL; Arenas, Monica; Borchuluun, Maitsetseg et al

Poster (2023, June 06)

The complex processes of heterogeneous reactions of granular materials such as occurring during metals-ore reduction or biomass gasification involve numerous physical phenomena. The combination of ... [more ▼]

The complex processes of heterogeneous reactions of granular materials such as occurring during metals-ore reduction or biomass gasification involve numerous physical phenomena. The combination of elevated temperature, complex flow, aggressive atmosphere and heterogeneous chemistry make it difficult to study these industrial processes. One of the most important aspects f heterogeneous reactions is to understand and quantify the evolution of the different transformations. For instance, during metal-oxides reduction processes, it is of high importance to quantify the rate at which the pure metal is formed. Nevertheless, it is almost impossible, by experimental means only, to separately observe, accurately quantify and gain insight into these mingled nonlinear physical and chemical processes. In the last decade, numerical simulation tools for particulate processes, such as the eXtended Discrete Element Method (XDEM), have become indispensable to study complex systems without the need of costly experimental practices. In the past, the XDEM has been employed to predict the reduction of tungsten trioxide (WO 3) in dry hydrogen (H2) atmospheres [1] and reduction of iron ores [2]. In the before-mentioned research works, it was employed kinetic data extracted from literature. On one hand, in these processes the kinetic data differ from each other. This is due to the fact that the experimental data in the literature is interpreted with lumped models and empirical models bonded to the specific experimental conditions. On the other hand, advanced simulation tools, such as XDEM, account for all the influencing phenomena (e.g. species and energy distribution, flow conditions, particles shape, rheological properties) constantly interacting in time and space. In these advanced simulation tools, each particle is treated and solved as individual entities and an accurate prediction of the species formation and transport in time and space is provided. Thus, in such advanced numerical tools, the reaction rate parameters representative of the kinetics alone of the involved chemical reactions must be employed. In this contribution, two XDEM simulation case studies accounting for the industrial reduction of WO 3 are presented. The first case study is employed to determine the reaction rate parameters of the four prevalent reduction steps (WO 3↔WO2.9↔WO2.72↔WO2↔W) upon the H 2 reduction of O3. Where the reaction rates are modeled following an Arrhenius law with two parameters per step i.e. pre-exponential factor and activation energy). The constituted optimization problem of minimization of error of the XDEM simulations vs experimental data, implemented and solved in a High Performance Computing (HPC) cluster, is presented and discussed. The determined parameters are later assessed by comparison to a secondly presented case study. [less ▲]

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See detailToward High-Performance Multi-Physics Coupled Simulations for the Industry with XDEM
Besseron, Xavier UL; Adhav, Prasad UL; Louw, Daniel Louis UL et al

Scientific Conference (2023, June 01)

Computational simulation is an essential tool for researchers and scientific engineers to set up and explore experimental processes. Industrial applications drive the need for larger models and finer ... [more ▼]

Computational simulation is an essential tool for researchers and scientific engineers to set up and explore experimental processes. Industrial applications drive the need for larger models and finer accuracy that require an increased amount of computation which motivates the use of HPC platforms to perform the simulations. In our work, we focus on multi-physics simulations with particle-fluid interactions. We developed the XDEM (eXtended Discrete Element Method) framework which simulates the motion and thermodynamic state of particles, and is coupled with independent Computational Fluid Dynamics (CFD) solvers for the simulation of fluids. This coupled multi-physics solution has successfully been used in a wide variety of industrial applications to simulate biomass combustion, blast furnace reduction processes or abrasive water jet cutting. In this presentation, we give an overview of the different techniques used in the XDEM software to simulate complex industrial processes on HPC platforms and how we make it available seamlessly to users: The coupling between the particles and fluid phases is designed to be flexible and follows a modular design in which each component is replaceable. In this approach, the particle phase is represented in the fluid domain by field values (e.g. porosity, heat and mass sources) that are added to the CFD models. It relies on the preCICE coupling library which is responsible for the data mapping, interpolation and communication. Because the coupling of particles within a fluid is a volume coupling (as opposed to surface coupling), it requires a significant amount of data to be exchanged. To address this issue, we have designed coupling-aware partitioning strategies that account for the workload and data distribution of all participants in order to reduce inter-process communication. Finally, we developed an automated scientific workflow to simplify the execution of these coupled simulations for non-HPC-expert end-users. Based on an all-in-one Singularity image, it takes care of all the steps: preparation of the input, execution on an HPC platform, and analysis of the results. This workflow has been cloudified as part of the CloudiFacturing project. With these developments, we put together the bricks necessary to provide flexible and turnkey multi-physics coupled simulation for industrial end-users that leverage the performance of HPC platforms. [less ▲]

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See detailInstalling Scientific Software on HPC with EasyBuild
Besseron, Xavier UL

Scientific Conference (2023, May 19)

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

Scientific Conference (2023, May 19)

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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See detailPractical Debugging & Performance Engineering for High Performance Computing
Besseron, Xavier UL

Scientific Conference (2023, May 17)

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See detailThree-dimensional CFD-DEM simulation of raceway transport phenomena in a blast furnace
Aminnia, Navid UL; Adhav, Prasad UL; Darlik, Fateme UL et al

in Fuel (2023), 334(2),

Improving energy efficiency in a blast furnace (BF) has a significant effect on energy consumption and pollutant emission in a steel plant. In the BF, the blast injection creates a cavity, the so-called ... [more ▼]

Improving energy efficiency in a blast furnace (BF) has a significant effect on energy consumption and pollutant emission in a steel plant. In the BF, the blast injection creates a cavity, the so-called raceway, near the inlet. On the periphery of the raceway, a ring-type zone is formed which is associated with the highest coke combustion rate and temperatures in the raceway. Therefore, predicting the raceway size or in other words, the periphery of the ring-type zone with accuracy is important for estimating the BF’s energy and coke consumption. In the present study, Computational Fluid Dynamics (CFD) is coupled to Discrete Element Method (DEM) to develop a three-dimensional (3D) model featuring a gas–solid reacting flow, to study the transport phenomena inside the raceway. The model is compared to a previously developed two-dimensional (2D) model and it is shown that the assumptions associated with a 2D model, result in an overestimation of the size of the raceway. The 3D model is then used to investigate the coke particles’ combustion and heat generation and distribution in the raceway. It is shown that a higher blast flow rate is associated with a higher reaction rate and a larger raceway. A 10% increase in the inlet velocity (from 200 m/s to 220 m/s) caused the raceway volume to grow by almost 40%. The DEM model considers a radial discretization over the particle, therefore the heat and mass distributions over the particle are analyzed as well. [less ▲]

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See detailInvestigation of OpenFOAM-XDEM momentum coupling results for AWJC Nozzle using preCICE
Adhav, Prasad UL; Besseron, Xavier UL; Peters, Bernhard UL

Scientific Conference (2023, February 14)

The high-speed water jet is the momentum source in an Abrasive Water Jet Cutting Nozzle. This momentum is transferred to the abrasive particles & the air within the nozzle. This leads to turbulent ... [more ▼]

The high-speed water jet is the momentum source in an Abrasive Water Jet Cutting Nozzle. This momentum is transferred to the abrasive particles & the air within the nozzle. This leads to turbulent & complex particle-laden flow in the nozzle. These flow conditions can influence particle impacts on the nozzle, thus influencing erosion. Hence it is imperative that this complex particle-laden flow is captured correctly. The momentum exchange can be directly from the water jet to the particles or indirectly through the airflow. In this work, we investigate these fluid-particle momentum exchanges. Our prototype uses preCICE for volumetric coupling of XDEM (for the particle motion), & OpenFOAM (for the fluid). XDEM uses fluid flow conditions to compute the forces acting on particles. XDEM computes the particle momentum source that is injected into the fluid solver. The results of the coupled simulation align with literature & can be extended to include the FEM component for erosion predictions. [less ▲]

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

Scientific Conference (2022, December 09)

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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See detailLocal Verlet buffer approach for broad-phase interaction detection in Discrete Element Method
Mainassara Chekaraou, Abdoul Wahid UL; Besseron, Xavier UL; Rousset, Alban UL et al

E-print/Working paper (2022)

The Extended Discrete Element Method (XDEM) is an innovative numerical simulation technique that extends the dynamics of granular materials known as Discrete Element Method (DEM) by additional properties ... [more ▼]

The Extended Discrete Element Method (XDEM) is an innovative numerical simulation technique that extends the dynamics of granular materials known as 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 complexes and heavy in computation time. At each time step, those simulations generate a list of interacting particles and this phase is one of the most computationally expensive parts of a DEM simulation. The Verlet buffer method, initially introduced in Molecular Dynamic (MD) (and also used in DEM), allows keeping the interaction list for many time steps by extending each particle neighbourhood by a certain extension range, and thus broadening the interaction list. The method relies on the temporal coherency of DEM, which guarantees that no particles move erratically from one time step to the next. In the classical approach, all the particles have their neighbourhood extended by the same value which leads to suboptimal performances in simulations where different flow regimes coexist. Additionally, and unlike in MD, there is no comprehensive study analysing the different parameters that affect the performance of the Verlet buffer method in DEM. In this work, we propose a new method for the dynamic update of the neighbour list that depends on the particles individual displacement and define a particle-specific extension range based on the local flow regime. The interaction list is analysed throughout the simulation based on the particle's displacement allowing a flexible update according to the flow regime conditions. We evaluate the influence of the Verlet extension range on the execution time through different test cases and analyse empirically the extension range value giving the best performance. [less ▲]

Detailed reference viewed: 278 (87 UL)
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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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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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See detailAn Innovative Partitioning Technology for Coupled Software Modules
Peters, Bernhard UL; Besseron, Xavier UL; Peyraut, Alice et al

in Proceedings of the 12th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - SIMULTECH (2022, July)

Multi-physics simulation approaches by coupling various software modules is paramount to unveil the underlying physics and thus leads to an improved design of equipment and a more efficient operation ... [more ▼]

Multi-physics simulation approaches by coupling various software modules is paramount to unveil the underlying physics and thus leads to an improved design of equipment and a more efficient operation. These simulations are in general to be carried out on small to massively parallelised computers for which highly efficient partitioning techniques are required. An innovative partitioning technology is presented that relies on a co-located partitioning of overlapping simulation domains meaning that the overlapping areas of each simulation domain are located at one node. Thus, communication between modules is significantly reduced as compared to an allocation of overlapping simulation domains on different nodes. A co-located partitioning reduces both memory and inter-process communication. [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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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 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 ▲]

Detailed reference viewed: 163 (14 UL)