Shen Zhang, Nan Gui, Yiyang Luo, Xingtuan Yang, Shengyao Jiang
{"title":"采用粗单元对稀大颗粒CFD-DEM中阻力计算的改进:阻力分布的有效投影面积","authors":"Shen Zhang, Nan Gui, Yiyang Luo, Xingtuan Yang, Shengyao Jiang","doi":"10.1016/j.partic.2025.08.013","DOIUrl":null,"url":null,"abstract":"<div><div>This study addresses a critical challenge in CFD-DEM simulations: the accurate assignment of drag force to fluid mesh cells when the cell size exceeds particle sizes. Traditional particle centroid method (PCM) approaches often lead to abrupt drag force variations as particles cross cell boundaries due to their discrete nature. To overcome this limitation, we propose a novel algorithm that computes an analytical solution for the effective projected area (EPA) of particles within computational cells, aligned with the relative velocity direction. The drag force is then proportionally scaled according to this EPA calculation. The paper presents a specific implementation case of our algorithm, focusing on scenarios where a cell vertex resides within a particle boundary. For EPA determination, we introduce an innovative classification approach based on face-windward surface relations. Extensive validation involved 100,000 test cases with varying cell-particle relative positions (all constrained by the vertex-in-particle condition), systematically classified into 18 types using our scheme. Results demonstrate that all computed EPA values remain within theoretical bounds, confirming the classification's comprehensiveness. Through 5 classic particle movement simulations, we show that our method maintains continuous EPA variation across time steps - a marked improvement over PCM's characteristic discontinuities. Implementation within the CFD-DEM framework for single-particle sedimentation yields terminal velocities that closely match experimental data while ensuring smooth drag force transitions between fluid cells. Compared to PCM, the present method reduces the relative error in terminal settling velocity by approximately 43 %. Moreover, comparative studies of dual-particle sedimentation demonstrate our algorithm's superior performance relative to conventional PCM approaches. For Particle 1, the terminal vertical velocity predicted by the present method reduces the relative error by approximately 17 % compared to PCM. These advances significantly enhance simulation fidelity for particle-fluid interaction problems where cell-particle size ratios challenge traditional methods.</div></div>","PeriodicalId":401,"journal":{"name":"Particuology","volume":"105 ","pages":"Pages 340-356"},"PeriodicalIF":4.3000,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improved drag force calculation in CFD-DEM using coarse cell for dilute large-sized particles: Effective projected area for drag force distribution\",\"authors\":\"Shen Zhang, Nan Gui, Yiyang Luo, Xingtuan Yang, Shengyao Jiang\",\"doi\":\"10.1016/j.partic.2025.08.013\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study addresses a critical challenge in CFD-DEM simulations: the accurate assignment of drag force to fluid mesh cells when the cell size exceeds particle sizes. Traditional particle centroid method (PCM) approaches often lead to abrupt drag force variations as particles cross cell boundaries due to their discrete nature. To overcome this limitation, we propose a novel algorithm that computes an analytical solution for the effective projected area (EPA) of particles within computational cells, aligned with the relative velocity direction. The drag force is then proportionally scaled according to this EPA calculation. The paper presents a specific implementation case of our algorithm, focusing on scenarios where a cell vertex resides within a particle boundary. For EPA determination, we introduce an innovative classification approach based on face-windward surface relations. Extensive validation involved 100,000 test cases with varying cell-particle relative positions (all constrained by the vertex-in-particle condition), systematically classified into 18 types using our scheme. Results demonstrate that all computed EPA values remain within theoretical bounds, confirming the classification's comprehensiveness. Through 5 classic particle movement simulations, we show that our method maintains continuous EPA variation across time steps - a marked improvement over PCM's characteristic discontinuities. Implementation within the CFD-DEM framework for single-particle sedimentation yields terminal velocities that closely match experimental data while ensuring smooth drag force transitions between fluid cells. Compared to PCM, the present method reduces the relative error in terminal settling velocity by approximately 43 %. Moreover, comparative studies of dual-particle sedimentation demonstrate our algorithm's superior performance relative to conventional PCM approaches. For Particle 1, the terminal vertical velocity predicted by the present method reduces the relative error by approximately 17 % compared to PCM. 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Improved drag force calculation in CFD-DEM using coarse cell for dilute large-sized particles: Effective projected area for drag force distribution
This study addresses a critical challenge in CFD-DEM simulations: the accurate assignment of drag force to fluid mesh cells when the cell size exceeds particle sizes. Traditional particle centroid method (PCM) approaches often lead to abrupt drag force variations as particles cross cell boundaries due to their discrete nature. To overcome this limitation, we propose a novel algorithm that computes an analytical solution for the effective projected area (EPA) of particles within computational cells, aligned with the relative velocity direction. The drag force is then proportionally scaled according to this EPA calculation. The paper presents a specific implementation case of our algorithm, focusing on scenarios where a cell vertex resides within a particle boundary. For EPA determination, we introduce an innovative classification approach based on face-windward surface relations. Extensive validation involved 100,000 test cases with varying cell-particle relative positions (all constrained by the vertex-in-particle condition), systematically classified into 18 types using our scheme. Results demonstrate that all computed EPA values remain within theoretical bounds, confirming the classification's comprehensiveness. Through 5 classic particle movement simulations, we show that our method maintains continuous EPA variation across time steps - a marked improvement over PCM's characteristic discontinuities. Implementation within the CFD-DEM framework for single-particle sedimentation yields terminal velocities that closely match experimental data while ensuring smooth drag force transitions between fluid cells. Compared to PCM, the present method reduces the relative error in terminal settling velocity by approximately 43 %. Moreover, comparative studies of dual-particle sedimentation demonstrate our algorithm's superior performance relative to conventional PCM approaches. For Particle 1, the terminal vertical velocity predicted by the present method reduces the relative error by approximately 17 % compared to PCM. These advances significantly enhance simulation fidelity for particle-fluid interaction problems where cell-particle size ratios challenge traditional methods.
期刊介绍:
The word ‘particuology’ was coined to parallel the discipline for the science and technology of particles.
Particuology is an interdisciplinary journal that publishes frontier research articles and critical reviews on the discovery, formulation and engineering of particulate materials, processes and systems. It especially welcomes contributions utilising advanced theoretical, modelling and measurement methods to enable the discovery and creation of new particulate materials, and the manufacturing of functional particulate-based products, such as sensors.
Papers are handled by Thematic Editors who oversee contributions from specific subject fields. These fields are classified into: Particle Synthesis and Modification; Particle Characterization and Measurement; Granular Systems and Bulk Solids Technology; Fluidization and Particle-Fluid Systems; Aerosols; and Applications of Particle Technology.
Key topics concerning the creation and processing of particulates include:
-Modelling and simulation of particle formation, collective behaviour of particles and systems for particle production over a broad spectrum of length scales
-Mining of experimental data for particle synthesis and surface properties to facilitate the creation of new materials and processes
-Particle design and preparation including controlled response and sensing functionalities in formation, delivery systems and biological systems, etc.
-Experimental and computational methods for visualization and analysis of particulate system.
These topics are broadly relevant to the production of materials, pharmaceuticals and food, and to the conversion of energy resources to fuels and protection of the environment.