Reference : Parallel Multi-Physics Simulation of Biomass Furnace and Cloud-based Workflow for SMEs
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
Computational Sciences
http://hdl.handle.net/10993/50676
Parallel Multi-Physics Simulation of Biomass Furnace and Cloud-based Workflow for SMEs
English
Besseron, Xavier mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE) >]
Rusche, Henrik []
Peters, Bernhard mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE) >]
Jul-2022
Practice and Experience in Advanced Research Computing (PEARC '22)
Association for Computing Machinery
Yes
No
International
9781450391610
New York, NY
USA
Practice & Experience in Advanced Research Computing
July 10-14, 2022
Boston, MA
USA
[en] Biomass combustion ; Multi-physics simulation ; CFD-DEM ; Parallel coupling ; Cloudification
[en] 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.
University of Luxembourg: Luxembourg XDEM Research Centre - LuXDEM
Researchers ; Professionals
http://hdl.handle.net/10993/50676
10.1145/3491418.3530294
https://pearc.acm.org/pearc22/
H2020 ; 768892 - CloudiFacturing - Cloudification of Production Engineering for Predictive Digital Manufacturing

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