4.7 Article

Calibration and uniqueness analysis of microparameters for DEM cohesive granular material

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ELSEVIER
DOI: 10.1016/j.ijmst.2021.11.003

关键词

Discrete element method (DEM); Particle flow code (PFC); Differential evolution (DE); Parameter calibration; Uniqueness analysis; Post-peak behaviour

资金

  1. China Scholarship Council (CSC)
  2. University of Queensland

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The DE algorithm is used to calibrate microparameters of the DEM cohesive granular material. The calibrated results reveal the correlation between microparameters and the material's mechanical behavior. Consideration of more macroparameters is highlighted for future study.
The differential evolution (DE) algorithm was deployed to calibrate microparameters of the DEM cohesive granular material. 4 macroparameters, namely, uniaxial compressive strength, direct tensile strength, Young's modulus and Poisson's ratio, can be calibrated to high accuracy. The best calibration accuracy could reach the sum of relative errors REsum < 0.1%. Most calibrations can be achieved with REsum < 5% within hours or REsum < 1% within 2 days. Based on the calibrated results, microparameters uniqueness analysis was carried out to reveal the correlation between microparameters and the macroscopic mechanical behaviour of material: (1) microparameters effective modulus, tensile strength and normal-to-shear stiffness ratio control the elastic behaviour and stable crack growth, (2) microparame-ters cohesion and friction angles present a negative linear correlation that controls the axial strain and lateral strain prior to the peak stress, and (3) microparameters friction coefficient controls shear crack friction and slip mainly refers to the unstable crack behaviour. Consideration of more macroparameters to regulate the material mechanical behaviour that is dominated by shear crack and slip motion is high-lighted for future study. The DE calibration method is expected to serve as an alternative method to cal-ibrate the DEM cohesive granular material to its peak strength. (C) 2021 Published by Elsevier B.V. on behalf of China University of Mining & Technology.

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