Mapping strategies for unresolved CFD-DEM modeling of fluid-solid flows: Latest developments and perspectives--颗粒学报PARTICUOLOGY

Zhou, L., Li, Z., Luo, Z.-H., & Zhu, L.-T. (2026). Mapping strategies for unresolved CFD-DEM modeling of fluid-solid flows: Latest developments and perspectives. Particuology, 108, 41-53. https://doi.org/10.1016/j.partic.2025.11.008

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

Lianyong Zhou^a, Zhongmei Li^b, Zheng-Hong Luo^c *, Li-Tao Zhu^{a d *}

a College of Smart Energy, Shanghai Jiao Tong University, Shanghai, 200240, China
b Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai, 200237, China
c Department of Chemical Engineering, School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
d State Key Laboratory of Polyolefins and Catalysis, Shanghai Key Laboratory of Catalysis Technology for Polyolefins, Shanghai Jiao Tong University, Shanghai, 200240, China

10.1016/j.partic.2025.11.008

Volume 108, January 2026, Pages 41-53

Received 7 September 2025, Revised 10 November 2025, Accepted 16 November 2025, Available online 20 November 2025, Version of Record 3 December 2025.

E-mail: luozh@sjtu.edu.cn; sjtu_zlt@sjtu.edu.cn

Highlights

• A systematic perspective on mapping strategies for unresolved CFD-DEM modeling.

• Summarize and analyze the merits and limitations of local, non-local, and two-step mapping schemes.

• Identify key challenges and future directions of developing novel mapping schemes.

Abstract

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.

Graphical abstract

Keywords

CFD-DEM; Fluid-solid flows; Mapping strategies; Grid-to-particle size ratio

文章导读