Automated discrete element method calibration using genetic and optimization algorithms
EPJ Web Conf., 140 (2017) 15011
Published online: 2017-06-30
Articles citing this article
The Citing articles tool gives a list of articles citing the current article.
The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program. You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).
Cited article:
This article has been cited by the following article(s):
Three-Dimensional Discrete Element Modeling for the Angle of Repose of Granular Materials: Artificial Intelligence and Machine Learning Approach
Yassir Mubarak Hussein Mustafa, Hamzah M. B. Al-Hashemi, Omar Saeed Baghabra Al-Amoudi and Omar Hamdi JasimArabian Journal for Science and Engineering (2025)
https://doi.org/10.1007/s13369-024-09942-2
Application of Bayesian network and genetic algorithm enhanced Monte Carlo method in urban transportation infrastructure investment
Maojiao Wang and Shanchuan YuJournal of Computational Methods in Sciences and Engineering (2025)
https://doi.org/10.1177/14727978241313262
A calibration framework for DEM models based on the stress‒strain curve of uniaxial compressive tests by using the AEO algorithm and several calibration suggestions
Min Wang, Zhenxing Lu, Yanlin Zhao and Wen WanComputational Particle Mechanics 12 (1) 541 (2025)
https://doi.org/10.1007/s40571-024-00820-0
Calibrating microparameters of DEM models by using CEM, DE, EFO, MFO, SSO algorithms and the optimal hyperparameters
Min Wang, Zhenxing Lu, Yanlin Zhao and Wen WanComputational Particle Mechanics 11 (2) 839 (2024)
https://doi.org/10.1007/s40571-023-00656-0
Measuring and modelling of soil displacement from a horizontal penetrometer and a sweep using an IMU sensor fusion and DEM
László Pásthy, Bence Szabó and Kornél TamásSoil and Tillage Research 244 106207 (2024)
https://doi.org/10.1016/j.still.2024.106207
41 (2023)
https://doi.org/10.1002/9783527835935.ch2
A Multi-Objective Identification of DEM Microparameters for Brittle Materials
Rui Chen, Xu Wang, Xiangwu Xiao, Congfang Hu, Ruitao Peng and Yong WangCrystals 12 (3) 387 (2022)
https://doi.org/10.3390/cryst12030387
Replicating cohesive and stress-history-dependent behavior of bulk solids: Feasibility and definiteness in DEM calibration procedure
M. Javad Mohajeri, Cees van Rhee and Dingena L. SchottAdvanced Powder Technology 32 (5) 1532 (2021)
https://doi.org/10.1016/j.apt.2021.02.044
A calibration framework for the microparameters of the DEM model using the improved PSO algorithm
Min Wang, Zhenxing Lu, Wen Wan and Yanlin ZhaoAdvanced Powder Technology 32 (2) 358 (2021)
https://doi.org/10.1016/j.apt.2020.12.015
Strength of industrial sandstones modelled with the Discrete Element Method
Piotr Klejment, Robert Dziedziczak and Paweł ŁukaszewskiStudia Geotechnica et Mechanica 43 (4) 346 (2021)
https://doi.org/10.2478/sgem-2021-0020
Systematic design optimization of grabs considering bulk cargo variability
M. Javad Mohajeri, Arjan J. van den Bergh, Jovana Jovanova and Dingena L. SchottAdvanced Powder Technology 32 (5) 1723 (2021)
https://doi.org/10.1016/j.apt.2021.03.027
Application of supervised machine learning as a method for identifying DEM contact law parameters
Piotr KlejmentMathematical Biosciences and Engineering 18 (6) 7490 (2021)
https://doi.org/10.3934/mbe.2021370
2770 (2020)
https://doi.org/10.1109/ICRA40945.2020.9197063
Improved analytical energy balance model for evaluating agglomeration from a binary collision of identical wet particles
Jaber Shabanian, Marc A. Duchesne, Allan Runstedtler, Madhava Syamlal and Robin W. HughesChemical Engineering Science 223 115738 (2020)
https://doi.org/10.1016/j.ces.2020.115738
DEM modelling for flow of cohesive lignocellulosic biomass powders: Model calibration using bulk tests
John Pachón-Morales, Huy Do, Julien Colin, et al.Advanced Powder Technology 30 (4) 732 (2019)
https://doi.org/10.1016/j.apt.2019.01.003
Benefits of virtual calibration for discrete element parameter estimation from bulk experiments
Salma Ben Turkia, Daniel N. Wilke, Patrick Pizette, Nicolin Govender and Nor-Edine AbriakGranular Matter 21 (4) (2019)
https://doi.org/10.1007/s10035-019-0962-y
Calibration of Discrete-Element-Method Parameters for Cohesive Materials Using Dynamic-Yield-Strength and Shear-Cell Experiments
Subhodh Karkala, Nathan Davis, Carl Wassgren, Yanxiang Shi, Xue Liu, Christian Riemann, Gary Yacobian and Rohit RamachandranProcesses 7 (5) 278 (2019)
https://doi.org/10.3390/pr7050278
On the challenges facing the handling of solid biomass feedstocks
Dusan Ilic, Kenneth Williams, Richard Farnish, Erin Webb and Gary LiuBiofuels, Bioproducts and Biorefining 12 (2) 187 (2018)
https://doi.org/10.1002/bbb.1851