Automated discrete element method calibration using genetic and optimization algorithms
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, ar...
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Published in | EPJ Web of Conferences Vol. 140; p. 15011 |
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Main Authors | , , |
Format | Journal Article Conference Proceeding |
Language | English |
Published |
Les Ulis
EDP Sciences
01.01.2017
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Subjects | |
Online Access | Get full text |
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Summary: | 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. |
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ISSN: | 2100-014X 2101-6275 2100-014X |
DOI: | 10.1051/epjconf/201714015011 |