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A particle-resolved heat-particle-fluid coupling model by DEM-IMB-LBM
Journal of Rock Mechanics and Geotechnical Engineering
Swansea University Authors: Jinlong Fu , Yuntian Feng
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DOI (Published version): 10.1016/j.jrmge.2023.02.030
Multifield coupling is frequently encountered and also an active area of research in geotechnical engineering. In this work, a particle-resolved direct numerical simulation (PR-DNS) technique is extended to simulate particle-fluid interaction problems involving heat transfer at the grain level. In t...
|Published in:||Journal of Rock Mechanics and Geotechnical Engineering|
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Multifield coupling is frequently encountered and also an active area of research in geotechnical engineering. In this work, a particle-resolved direct numerical simulation (PR-DNS) technique is extended to simulate particle-fluid interaction problems involving heat transfer at the grain level. In this extended technique, an immersed moving boundary scheme (IMB) is used to couple the discrete element method (DEM) and lattice Boltzmann method (LBM), while a recently proposed Dirichlet-type thermal boundary condition is also adapted to account for heat transfer between fluid phase and solid particles. The resulting DEM-IBM-LBM model is robust to simulate moving curved boundaries with constant temperature in thermal flows. To facilitate the understanding and implementation of this coupled model for non-isothermal problems, a complete list is given for the conversion of relevant physical variables to lattice units. Then, benchmark tests, including a single-particle sedimentation and a two-particle drafting-kissing-tumbling (DKT) simulation with heat transfer, are carried out to validate the accuracy of our coupled technique. To further investigate the role of heat transfer in particle-laden flows, two multiple-particle problems with heat transfer are performed. Numerical examples demonstrate that the proposed coupling model is a promising high-resolution approach for simulating the heat-particle-fluid coupling at the grain level.
Faculty of Science and Engineering
This work is financially supported by the National Natural Science Foundation of China (Nos. 11702235, 51641905, 51874144, 42077254), the support of EPSRC Grant (UK): PURIFY (EP/V000756/1), the Impact Funding (Swansea University), the Natural Science Foundation of Hunan Province (No. 2022JJ30567), the Scientific Research Foundation of Education Department of Hunan Province, China (No. 20B557), and the High-level Talent Gathering Project in Hunan Province, China (No. 2019RS1059).