Optimized differential evolution algorithm for solving DEM material calibration problem

被引:0
|
作者
Songtao Ji
Jurij Karlovšek
机构
[1] The University of Queensland,Geotechnical Engineering Centre, School of Civil Engineering
来源
Engineering with Computers | 2023年 / 39卷
关键词
Discrete element method (DEM); Particle flow code (PFC); Micro parameter calibration; Differential evolution (DE); Parameter optimization;
D O I
暂无
中图分类号
学科分类号
摘要
The discrete element method (DEM) micro parameter calibration has been a longstanding problem since the DEM was created. To date, the low-precision and time-consuming calibration procedures still pose difficulties for DEM applications. This study proposed an optimized differential evolution calibration method (OpDEC) to calibrate cohesive granular DEM material to the target macro mechanical properties. Macro parameter Young’s modulus, Poisson’s ratio, uniaxial compressive strength, and direct tensile strength can be calibrated to less than 5% weighted relative error within 5 h or less than 1% weighted relative error within 12.5 h. For this purpose, 180 calibrations were carried out to optimize the mutation strategy and control parameters of the differential evolution algorithm. A calibration evolutionary health monitoring scheme was devised to detect the possible ill calibrations in early time. The algorithm robustness was verified by 50 calibrations of 5 types of rock. Moreover, a laboratory-tested stress–strain curve of Äspö diorite was compared with 10 calibrated DEM models that showed a good agreement in terms of axial behaviour. The OpDEC has a great potential to serve as a fast and easy-to-implement method to calibrate the cohesive granular DEM material.
引用
收藏
页码:2001 / 2016
页数:15
相关论文
共 50 条
  • [1] Optimized differential evolution algorithm for solving DEM material calibration problem
    Ji, Songtao
    Karlovsek, Jurij
    ENGINEERING WITH COMPUTERS, 2023, 39 (03) : 2001 - 2016
  • [2] Solving Expensive Multimodal Optimization Problem by a Decomposition Differential Evolution Algorithm
    Gao, Weifeng
    Wei, Zhifang
    Gong, Maoguo
    Yen, Gary G.
    IEEE TRANSACTIONS ON CYBERNETICS, 2023, 53 (04) : 2236 - 2246
  • [3] A Differential Evolution Algorithm With Dual Populations for Solving Periodic Railway Timetable Scheduling Problem
    Zhong, Jing-Hui
    Shen, Meie
    Zhang, Jun
    Chung, Henry Shu-Hung
    Shi, Yu-Hui
    Li, Yun
    IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2013, 17 (04) : 512 - 527
  • [4] A Hybrid Differential Evolution Algorithm for Solving Function Optimization
    Zhou, Zhigang
    ADVANCED MEASUREMENT AND TEST, PARTS 1 AND 2, 2010, 439-440 : 315 - 320
  • [5] Calibration and uniqueness analysis of microparameters for DEM cohesive granular material
    Ji, Songtao
    Karlovsek, Jurij
    INTERNATIONAL JOURNAL OF MINING SCIENCE AND TECHNOLOGY, 2022, 32 (01) : 121 - 136
  • [6] Calibration of three-axis magnetometers with differential evolution algorithm
    Pang, Hongfeng
    Zhang, Qi
    Wang, Wei
    Wang, Junya
    Li, Ji
    Luo, Shitu
    Wan, Chengbiao
    Chen, Dixiang
    Pan, Mengchun
    Luo, Feilu
    JOURNAL OF MAGNETISM AND MAGNETIC MATERIALS, 2013, 346 : 5 - 10
  • [7] A hybrid differential evolution algorithm for solving nonlinear bilevel programming with linear constraints
    Zhu, Xiaobo
    Yu, Qian
    Wang, Xianjia
    PROCEEDINGS OF THE FIFTH IEEE INTERNATIONAL CONFERENCE ON COGNITIVE INFORMATICS, VOLS 1 AND 2, 2006, : 126 - 131
  • [8] A differential evolution algorithm for solving mixed-integer nonlinear programming problems
    Molina-Perez, Daniel
    Mezura-Montes, Efren
    Portilla-Flores, Edgar Alfredo
    Vega-Alvarado, Eduardo
    Calva-Yanez, Barbara
    SWARM AND EVOLUTIONARY COMPUTATION, 2024, 84
  • [9] A hybrid differential evolution algorithm for multiple container loading problem with heterogeneous containers
    Li, Xueping
    Zhang, Kaike
    COMPUTERS & INDUSTRIAL ENGINEERING, 2015, 90 : 305 - 313
  • [10] A calibration framework for the microparameters of the DEM model using the improved PSO algorithm
    Wang, Min
    Lu, Zhenxing
    Wan, Wen
    Zhao, Yanlin
    ADVANCED POWDER TECHNOLOGY, 2021, 32 (02) : 358 - 369