文献类型：期刊文献

英文题名：Mapping strategies for unresolved CFD-DEM modeling of fluid-solid flows: Latest developments and perspectives

作者：Zhou, Lianyong[1];Li, Zhongmei[2];Luo, Zheng-Hong[3];Zhu, Li-Tao[1,4]

机构：[1]Shanghai Jiao Tong Univ, Coll Smart Energy, Shanghai 200240, Peoples R China;[2]East China Univ Sci & Technol, Key Lab Smart Mfg Energy Chem Proc, Minist Educ, Shanghai 200237, Peoples R China;[3]Shanghai Jiao Tong Univ, Sch Chem & Chem Engn, Dept Chem Engn, Shanghai 200240, Peoples R China;[4]Shanghai Jiao Tong Univ, State Key Lab Polyolefins & Catalysis, Shanghai Key Lab Catalysis Technol Polyolefins, Shanghai 200240, Peoples R China

年份：2026

卷号：108

起止页码：41

外文期刊名：PARTICUOLOGY

收录：;EI(收录号：20254919656208);WOS:【SCI-EXPANDED(收录号:WOS:001634949400001)】；

基金：This work was supported by the National Natural Science Foundation of China (grant Nos. 22208208 and 22578267) , the Shanghai Magnolia Talent Plan Pujiang Project (grant No. 24PJD050) , the Shanghai Natural Science Foundation (grant No. 25ZR1402286) , and the Fundamental Research Funds for the Central University. The authors would like to thank the anonymous reviewers for their valuable comments, which are very helpful in improving this article. Our summary and analysis of the perspectives on mapping strategies in CFD-DEM simulations may not be entirely appropriate, but the primary goal is to provide some inspiration for readers in relevant fields.

语种：英文

外文关键词：CFD-DEM; Fluid-solid flows; Mapping strategies; Grid-to-particle size ratio

摘要：The accurate transfer of discrete particle information to continuum Eulerian fields, known as mapping or coarse-graining, plays a critical role in unresolved CFD-DEM modeling, governing both numerical stability and physical fidelity. Over the years, a variety of strategies have been proposed, spanning from local methods such as the satellite point scheme to non-local approaches based on kernel functions, diffusion, or hybrid formulations. Each method balances trade-offs between smoothness, conservation, computational efficiency, and applicability to complex grid configurations or non-spherical particles. This perspective summarizes the general methodology, representative implementations, and typical applications of existing mapping algorithms, and analyzes their respective merits and limitations. Particular attention is given to challenges associated with small grid-to-particle size ratios, irregular geometries, computational costs, and multi-physics coupling. Emerging directions, including adaptive and hybrid schemes, consistency with turbulence modeling, extensions to polydisperse and non-spherical particles, and machine learning-aided mapping acceleration, are discussed. Continued efforts in these areas promise to improve the robustness, accuracy, and scalability of CFD-DEM simulations, ultimately enabling more generalized and reliable modeling of complex multiphase flows in both research and industrial applications.