Automated discrete element method calibration using genetic and optimization algorithms

Conference paper (2017)

Authors

H.Q. Do Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering
A.M. Aragon Computational Design and Mechanics - Mechanical, Maritime and Materials Engineering
D.L. Schott Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering
Research Group
Transport Engineering and Logistics (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2017 H.Q. Do, A.M. Aragon, D.L. Schott
DOI: https://doi.org/10.1051/epjconf/201714015011
More Info
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Published Date

2017

Language

English

Faculty

Mechanical, Maritime and Materials Engineering

Department

Marine and Transport Technology

Research Group

Transport Engineering and Logistics

Abstract

This research aims at developing a universal methodology for automated calibration of microscopic properties of modelled granular materials. The proposed calibrator can be applied for different experimental set-ups. Two optimization approaches: (1) a genetic algorithm and (2) DIRECT optimization, are used to identify discrete element method input model parameters, e.g., coefficients of sliding and rolling friction. The algorithms are used to minimize the objective function characterized by the discrepancy between the experimental macroscopic properties and the associated numerical results. Two test cases highlight the robustness, stability, and reliability of the two algorithms used for automated discrete element method calibration with different set-ups.