^{Mei Xiao¹，Jiang Chuan¹，YuanBensen²，QiangHaiyan¹}

1.Logistics Engineering College， Shanghai Maritime University， Shanghai 201306， China；

2.Shanghai Yibo Electromechanical Equipment Co.， Ltd.， Shanghai 201401， China

Abstract

Objective Based on physical experiments and simulation tests， a collaborative calibration method for discrete element parameters is established for materials with different types and morphologies， and the particle scaling effect is taken into account. A high-fidelity parameter database for bulk materials is also constructed.

Methods The particle size distribution， angle of repose， and bulk density of materials with different types and morphologies were measured through physical experiments. Based on the measured parameters and the ranges of the parameters to be calibrated， a particle scaling model was used to determine the simulation parameter values required for discrete element simulation tests. The optimal parameter combination was further determined using Plackett-Burman tests， steepest ascent tests， Box-Behnken tests， and regression equations. Simulation tests were then conducted using the optimal parameter combination to determine the simulated angle of repose and bulk density. The simulation error between the simulated and experimental values was calculated to validate the calibration method for discrete element parameters.

Results and Discussion When discrete element particle models were established for granular， powdery， and mixed bulk materials， the scaling factor λ was set to 1 for soybean， maize， wheat， and paddy rice， whereas it was set to 5 for fly ash， lime powder， ammonium sulfate， and loose coal samples. The influence rate of the rolling friction coefficient between bulk materials on the angle of repose of different bulk materials was approximately 66.1%-99.7%， which was significantly higher than those of Poisson’s ratio， shear modulus， restitution coefficient between bulk materials， restitution coefficient between bulk material and steel， rolling friction coefficient between bulk material and steel， and JKR （Johnson-Kendall-Roberts） surface energy. The influence rate of JKR surface energy on powdery materials was approximately 12.9%-20.9%. The coefficients of determination （R²） of the regression models for all bulk materials were greater than 0.95， and the signal-to-noise ratios were greater than 4. The relative error between the simulated and experimental angles of repose was less than 3%， and that between the simulated and experimental bulk densities was less than 7%. The relative errors between simulated and experimental bulk density and angle of repose of all bulk materials were within a reasonable range.

Conclusion The angle-of-repose regression model shows a good fit and can accurately predict the variations in the angle of reposewith significant influencing factors. The bulk density simulation test effectively reproduces the experimental process of bulk materials from the initial state through falling to final deposition state. The simulated deposition profiles of all bulk materials are highly consistent with experimental deposition morphologies， indicating that the calibrated parameters can accurately reproduce the macroscopic flow behavior of real bulk materials and that the parameter values are reasonable and reliable.

Keywords： multi-morphology bulk material； particle scaling theory； discrete element parameter； angle of repose； bulk density； parameter calibration

Get Citation:Mei Xiao， Jiang Chuan， Yuan Bensen， et al. Collaborative calibration method and verification of discrete element parameters for multi-morphology bulk materials［J］. China PowderScience and Technology， 2026， 32（5）： 1-13.

Received: 2026-02-16， Revised:2026-05-07， Online：2026-06-16。

Funding： This research was supported by the National Natural Science Foundation of China (Grant No. 52502447) and Shanghai Pujiang Talent Program (Grant No. 21PJ1404600).

DOI：10.13732/j.issn.1008-5548.2026.05.013

CLC No.:TB4； TP391.9

Type Code:A

Serial No.:1008-5548（2026）05-0001-13