[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.
Centre de recherche :
LuXDEM - University of Luxembourg: Luxembourg XDEM Research Centre
Disciplines :
Sciences informatiques
Auteur, co-auteur :
BESSERON, Xavier ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)
Rusche, Henrik
PETERS, Bernhard ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
Parallel Multi-Physics Simulation of Biomass Furnace and Cloud-based Workflow for SMEs
Date de publication/diffusion :
juillet 2022
Nom de la manifestation :
Practice & Experience in Advanced Research Computing
Lieu de la manifestation :
Boston, MA, Etats-Unis
Date de la manifestation :
July 10-14, 2022
Manifestation à portée :
International
Titre de l'ouvrage principal :
Practice and Experience in Advanced Research Computing (PEARC '22)
Maison d'édition :
Association for Computing Machinery, New York, NY, Etats-Unis
Xavier Besseron, Alban Rousset, Alice Peyraut, and Bernhard Peters. 2021. Eulerian-Lagrangian Momentum Coupling between XDEM and OpenFOAM Using preCICE. In 14th WCCM & ECCOMAS Congress 2020.
Christian Bruch, Bernhard Peters, and Thomas Nussbaumer. 2003. Modelling Wood Combustion under Fixed Bed Conditions. Fuel 82 (2003). https://doi.org/10.1016/S0016-2361(02)00296-X
José María Cela, Philippe O. A. Navaux, Alvaro L. G. A. Coutinho, and Rafael Mayo-García. 2016. Fostering Collaboration in Energy Research and Technological Developments Applying New Exascale HPC Techniques. In 16th IEEE/ACM Int. Symp. on Cluster, Cloud and Grid Comp. (CCGrid). https://doi.org/10.1109/CCGrid.2016.51
Tao Chen, Xiaoke Ku, Jianzhong Lin, and Hanhui Jin. 2019. Modelling the Combustion of Thermally Thick Biomass Particles. Powder Technology 353 (2019). https://doi.org/10.1016/j.powtec.2019.05.011
Gerasimos Chourdakis, Kyle Davis, Benjamin Rodenberg, Miriam Schulte, Frédéric Simonis, Benjamin Uekermann, Georg Abrams, Hans-Joachim Bungartz, Lucia Cheung Yau, Ishaan Desai, Konrad Eder, Richard Hertrich, Florian Lindner, Alexander Rusch, Dmytro Sashko, David Schneider, Amin Totounferoush, Dominik Volland, Peter Vollmer, and Oguz Ziya Koseomur. 2021. preCICE v2: A Sustainable and User-Friendly Coupling Library. ArXiv210914470 Cs (2021).
Ayhan Demirbas. 2005. Potential Applications of Renewable Energy Sources, Biomass Combustion Problems in Boiler Power Systems and Combustion Related Environmental Issues. Progress in Energy and Combustion Science 31 (2005). https://doi.org/10.1016/j.pecs.2005.02.002
Andrea Dernbecher, Alba Dieguez-Alonso, Andreas Ortwein, and Fouzi Tabet. 2019. Review on Modelling Approaches Based on Computational Fluid Dynamics for Biomass Combustion Systems. Biomass Conv. Bioref. 9 (2019). https://doi. org/10.1007/s13399-019-00370-z
Chiara Galletti, Niccolo Bitossi, Serena Santilli, Maria Grazia Gallo, Franco Sansone, and Bernhard Peters. 2017. Modeling of Biomass Combustion on a Reciprocating-Grate Super-Heater. In 40th Meeting of the Italian Section of the Comb. Inst. Italy. https://doi.org/10.4405/40proci2017.IX1
Xi Gao, Jia Yu, Liqiang Lu, and William A. Rogers. 2021. Coupling Particle Scale Model and SuperDEM-CFD for Multiscale Simulation of Biomass Pyrolysis in a Packed Bed Pyrolyzer. AIChE J. 67 (2021). https://doi.org/10.1002/aic.17139
Gabriel Fernando García Sánchez, Jorge Luis Chacón Velasco, Yesid Javier Rueda-Ordoñez, David Alfredo Fuentes Díaz, and Jairo René Martínez Morales. 2021. Solid Biomass Combustion Modeling: Bibliometric Analysis and Literature Review of the Latest Developments in OpenFOAM Based Simulations. Bioresource Technology Reports 15 (2021). https://doi.org/10.1016/j.biteb.2021.100781
Mohammad Hosseini Rahdar, Fuzhan Nasiri, and Bruno Lee. 2019. A Review of Numerical Modeling and Experimental Analysis of Combustion in Moving Grate Biomass Combustors. Energy Fuels 33 (2019). https://doi.org/10.1021/acs. energyfuels.9b02073
Shannon Keough. 2014. Optimising the Parallelisation of OpenFOAM Simulations. Technical Report. Maritime Division, Defence Science and Technology Organisation, Australia.
Tamas Kiss. 2019. A Cloud/HPC Platform and Marketplace for Manufacturing SMEs. In 11th Int. Workshop on Sci. Gateways (IWSG). Slovenia.
Mirjana Kljajic Borštnar and Tomi Ilijaš. 2019. Assessment of High Performance Computing Services Potential of SMEs. In 42nd Int. Conv. on Inf. and Comm. Tech., Electronics and Microelectronics (MIPRO). https://doi.org/10.23919/MIPRO.2019. 8756681
Gregory M. Kurtzer, Vanessa Sochat, and Michael W. Bauer. 2017. Singularity: Scientific Containers for Mobility of Compute. PLOS ONE 12 (2017). https://doi.org/10.1371/journal.pone.0177459
Christopher Lange, Patrick Barthelmäs, Tobias Rosnitschek, Stephan Tremmel, and Frank Rieg. 2021. Impact of HPC and Automated CFD Simulation Processes on Virtual Product Development-A Case Study. Appl. Sci. 11 (2021). https://doi.org/10.3390/app11146552
Liqiang Lu, Xi Gao, Jean-François Dietiker, Mehrdad Shahnam, and William A. Rogers. 2022. MFiX Based Multi-Scale CFD Simulations of Biomass Fast Pyrolysis: A Review. Chemical Engineering Science 248 (2022). https://doi.org/10.1016/j.ces. 2021.117131
Amir Houshang Mahmoudi, Xavier Besseron, Florian Hoffmann, Miladin Markovic, and Bernhard Peters. 2016. Modeling of the Biomass Combustion on a Forward Acting Grate Using XDEM. Chem. Eng. Sci. 142 (2016). https://doi.org/10.1016/j.ces.2015.11.015
Amir Houshang Mahmoudi, Florian Hoffmann, Bernhard Peters, and Xavier Besseron. 2016. Numerical Study of the Influence of Particle Size and Packing on Pyrolysis Products Using XDEM. Int. Comm. in Heat and Mass Transfer 71 (2016). https://doi.org/10.1016/j.icheatmasstransfer.2015.12.011
AbdoulWahid Mainassara Chekaraou, Alban Rousset, Xavier Besseron, Sébastien Varrette, and Bernhard Peters. 2018. Hybrid MPI+OpenMP Implementation of eXtended Discrete Element Method. In 30th Int. Symp. on Computer Architecture and High Performance Computing (SBAC-PAD 2018). https://doi.org/10.1109/CAHPC.2018.8645880
Mohammad Mohseni, Bernhard Peters, and Mehdi Baniasadi. 2017. Conversion Analysis of a Cylindrical Biomass Particle with a DEM-CFD Coupling Approach. Case Studies in Therm. Eng. 10 (2017). https://doi.org/10.1016/j.csite.2017.08.004
Corinna Netzer, Tian Li, Lars Seidel, Fabian Mauß, and Terese Løvås. 2020. Stochastic Reactor-Based Fuel Bed Model for Grate Furnaces. Energy Fuels 34 (2020). https://doi.org/10.1021/acs.energyfuels.0c02868
Nicole Paces and Martin Kozek. 2011. Modeling of a Grate-Firing Biomass Furnace for Real-Time Application. In Int. Symp. on Models and Modeling Methodologies in Sci. and Eng. (MMMse'11). Orlando, FL, USA.
Bernhard Peters. 2011. Validation of a Numerical Approach to Model Pyrolysis of Biomass and Assessment of Kinetic Data. Fuel 90 (2011). https://doi.org/10.1016/j.fuel.2011.02.003
Bernhard Peters, Maryam Baniasadi, Mehdi Baniasadi, Xavier Besseron, Alvaro A. Estupinan Donoso, Mohammad Mohseni, and Gabriele Pozzetti. 2019. XDEM Multi-Physics and Multi-Scale Simulation Technology: Review of DEM-CFD Coupling, Methodology and Engineering Applications. Particuology 44 (2019). https://doi.org/10.1016/j.partic.2018.04.005
Bernhard Peters, Alban Rousset, Xavier Besseron, Abdoul Wahid Mainassara Chekaraou, Maria Grazia Gallo, Franco Sansone, Alessio Lupi, and Chiara Galletti. 2020. Process Analysis in Thermal Process Engineering with High-Performance Computing Using the Example of Grate Firing. In 12th European Conf. on Industrial Furnaces and Boilers (INFUB-12). Porto, Portugal.
Gabriele Pozzetti, Xavier Besseron, Alban Rousset, and Bernhard Peters. 2018. A Co-Located Partitions Strategy for Parallel CFD-DEM Couplings. Adv. Powder Technol. 29 (2018). https://doi.org/10.1016/j.apt.2018.08.025
Frank Ulrich Rückert, Daniel Lehser-Pfeffermann, Danjana Theis, Ju Pyo Kim, Andre Schargen, Ingo Zorbach, and Jens Sohnemann. 2021. A New Simulation Model for Grate Firing Systems in OpenFOAM. Energy 216 (2021). https://doi.org/10.1016/j.energy.2020.119226
Salar Tavakkol, Niklas Weber, Thorsten Zirwes, Jordan Denev, and Henning Bockhorn. 2019. Performance of Large Scale Eulerian-Lagrangian Numerical Simulation for Particulate Flow in Rotating Reactors. In 6th bwHPC Symp. Karlsruhe, Germany.
Simon J. E. Taylor, Tamas Kiss, Anastasia Anagnostou, Gabor Terstyanszky, Peter Kacsuk, Joris Costes, and Nicola Fantini. 2018. The CloudSME Simulation Platform and Its Applications: A Generic Multi-Cloud Platform for Developing and Executing Commercial Cloud-Based Simulations. Fut. Gen. Comp. Sys. 88 (2018). https://doi.org/10.1016/j.future.2018.06.006
Christian Vecchiola, Suraj Pandey, and Rajkumar Buyya. 2009. High-Performance Cloud Computing: A View of Scientific Applications. In 10th Int. Symp. on Pervasive Systems, Algorithms, and Networks. https://doi.org/10.1109/I-SPAN.2009.150
Jingyuan Zhang, Tian Li, Henrik Ström, and Terese Løvås. 2020. Grid-Independent Eulerian-Lagrangian Approaches for Simulations of Solid Fuel Particle Combustion. Chemical Engineering Journal 387 (2020). https://doi.org/10.1016/j.cej.2019. 123964
Wenqi Zhong, Aibing Yu, Guanwen Zhou, Jun Xie, and Hao Zhang. 2016. CFD Simulation of Dense Particulate Reaction System: Approaches, Recent Advances and Applications. Chemical Engineering Science 140 (2016). https://doi.org/10.1016/j.ces.2015.09.035
