Discrete element model of cohesive material in a ring shear tester by applying genetic algorithms

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Abstract

In this research, DEM simulations are used to numerically replicate the behavior of cohesive coal in a ring shear tester. An automatic calibration procedure, based on the Non-dominated Sorting Genetic Algorithm, is applied to search for the appropriate simulation parameters such that its response is best fitted to the experimental macroscopic response. Using this calibration procedure, DEM input parameters are optimized successfully in reproducing the cohesive flowability of the coal sample. Through the case study of the ring shear tester, this research demonstrates the robustness and accuracy of the calibration framework using multi-objective optimization on multivariable calibration problems.
Original languageEnglish
Title of host publicationCHoPS 2018: 9th International Conference on Conveying and Handling of Particulate Solids
Number of pages7
Publication statusPublished - 2018
EventCHoPS 2018: 9th International Conference on Conveying and Handling of Particulate Solids - London, United Kingdom
Duration: 10 Sep 201814 Sep 2018

Conference

ConferenceCHoPS 2018: 9th International Conference on Conveying and Handling of Particulate Solids
CountryUnited Kingdom
CityLondon
Period10/09/1814/09/18

Keywords

  • Ring shear tester
  • DEM
  • Cohesive coal
  • Genetic algorithm (GA)
  • Optimization

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  • Cite this

    Do, H., Mohajeri, J., & Schott, D. (2018). Discrete element model of cohesive material in a ring shear tester by applying genetic algorithms. In CHoPS 2018: 9th International Conference on Conveying and Handling of Particulate Solids