A calibration framework for the microparameters of the DEM model using the improved PSO algorithm

• Published in: Advanced powder technology : the international journal of the Society of Powder Technology, Japan Vol. 32; no. 2; pp. 358 - 369
• Main Authors: Wang, Min, Lu, Zhenxing, Wan, Wen, Zhao, Yanlin
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.02.2021
• Subjects: Discrete element method (DEM); Improved particle swarm optimization algorithm (PSO); Macroparameters; Microparameters; Particle code flow; Particle code flow; Microparameters; Discrete element method (DEM); Macroparameters; Improved particle swarm optimization algorithm (PSO)
• ISSN: 0921-8831; 1568-5527
• DOI: 10.1016/j.apt.2020.12.015

[Display omitted] •The improved PSO was employed to calibrating the micro-parameters.•Different combinations of micro-parameters of DEM model can be obtained.•More macro-parameters should be used to calibrate the micro-parameters of DEM model. The discrete element method (DEM) is commonly used for simulating the mechanical characteristics of rock materials; however, constructing a DEM model requires the specification of a number of microparameters. In this paper, to obtain the microparameters of the DEM model, the improved particle swarm optimization (PSO) calibration method was presented. Based on numerical simulation examples, the new approach is considered valid for calibrating the microparameters of the DEM model. Moreover, it is concluded that different sets of microparameters can be determined when few macroparameters are used, which indicates that the empirical formula between microparameters and macroparameters is not reliable. From the analysis of the numerical simulation results, it is suggested that more macroparameters should be used to calibrate the microparameters of the DEM model, and the corresponding numerical simulation results could be more reliable; otherwise, the generated numerical model may not accurately simulate the mechanical characteristics of rock materials.