Print Email Facebook Twitter Automated discrete element method calibration using genetic and optimization algorithms Title Automated discrete element method calibration using genetic and optimization algorithms Author Do, H.Q. (TU Delft Transport Engineering and Logistics) Aragon, A.M. (TU Delft Computational Design and Mechanics) Schott, D.L. (TU Delft Transport Engineering and Logistics) Contributor Radjai, F. (editor) Nezamabadi, S. (editor) Luding, S. (editor) Delenne, J.Y. (editor) Date 2017 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. To reference this document use: http://resolver.tudelft.nl/uuid:393c7726-2eb5-4a8b-a653-18f86ad31ca6 DOI https://doi.org/10.1051/epjconf/201714015011 Publisher EDP Sciences, Les Ulis Cedex A, France Source Proceedings of the 8th International Conference on Micromechanics on Granular Media: Powders and Grains 2017 Event 8th International Conference on Micromechanics on Granular Media, 2017-07-03 → 2017-07-07, Montpellier, France Series EPJ Web of Conferences, 2100-014X, 140 Part of collection Institutional Repository Document type conference paper Rights © 2017 H.Q. Do, A.M. Aragon, D.L. Schott Files PDF epjconf162104.pdf 353.18 KB Close viewer /islandora/object/uuid:393c7726-2eb5-4a8b-a653-18f86ad31ca6/datastream/OBJ/view