A novel coupling method for unresolved CFD-DEM modelingShow others and affiliations
2023 (English)In: International Journal of Heat and Mass Transfer, ISSN 0017-9310, E-ISSN 1879-2189, Vol. 203, article id 123817Article in journal (Refereed) Published
Abstract [en]
In CFD-DEM (computational fluid dynamics-discrete element method) simulations particles are considered Lagrangian point particles. The details of the flow near the particle surface are therefore not fully resolved. When the particle scale is larger than the resolved flow scale, the coupling between the CFD model and the DEM model is critical. An effective coupling scheme should minimize the risk of artificial influences on the results from choices of numerical parameters in implementations and consider efficiency and robustness. In this work, a novel coupling method is developed. The method includes both the smoothing of the particle data and the sampling of the gas phase quantities. The smoothing employs the diffusion-based method. The gas sampling method can reconstruct the filtered fluid quantities at the particle center. The sampling method is developed based on the diffusion-based method with higher efficiency. The new method avoids mesh searching and it can be easily implemented in parallel computing. The developed method is validated by the simulation of a forced convection experiment for a fixed bed with steel spheres. With the well-posed grid-independent coupling scheme, the simulation results are in good agreement with the experimental measurements. The coupling effects and the computational cost are discussed in detail.
Place, publisher, year, edition, pages
Elsevier Ltd , 2023. Vol. 203, article id 123817
Keywords [en]
CFD, Coupling, DEM, Fixed bed, Forced convection, Diffusion in liquids, Efficiency, Coupling methods, Coupling scheme, Discrete element method simulations, Discrete elements method, Lagrangian points, Method model, Point-particles, Sampling method, Computational fluid dynamics
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:ri:diva-65504DOI: 10.1016/j.ijheatmasstransfer.2022.123817Scopus ID: 2-s2.0-85146016750OAI: oai:DiVA.org:ri-65504DiVA, id: diva2:1766454
Note
Funding details: Norges Forskningsråd, 267957, 294679; Funding details: Centre for Combustion Science and Technology, Faculty of Engineering, LTH, CECOST; Funding text 1: The authors acknowledge support from the Research Council of Norway and a number of industrial partners through the project BioCarbUp (294679) and Project GrateCFD (267957). NTNU IDUN/EPIC computing cluster provided high-performance computational resources for CFD simulations. Henrik Ström gratefully acknowledges co-financing from the Centre for Combustion Science and Technology (CECOST) and the Swedish Gasification Centre (SFC).
2023-06-132023-06-132023-06-13Bibliographically approved