Experiment and calibration of contact parameters of Mactra veneriformis based on DEM

Abstract

Mactra veneriformis represents the dominant species in China’s mudflat aquaculture. The discrete element model of M. veneriformis and its contact parameters serve as an important basis for the optimization design and simulation study of aquaculture and processing equipment. The contact parameters of the discrete element model of M. veneriformis were measured and calibrated by a combination of experimental testing and simulation calibration. The study measured the range of collision recovery, static, and rolling friction coefficients between M. veneriformis and stainless steel. The Plackett–Burman multifactorial significance screening test was then conducted for the split-cylinder method, the rotate-cylinder method, and the single-cylinder method particle characterization test methods. The ANOVA results were utilized to calibrate the contact parameters. The collision recovery coefficient of 0.29 between M. veneriformis–M. veneriformis and 0.28 between M. veneriformis–stainless steel. The coefficient of static friction of 0.41 was determined between M. veneriformis–M. veneriformis, a coefficient of static friction of 0.62 between M. veneriformis–stainless steel, and a coefficient of rolling friction of 0.23 between M. veneriformis–M. veneriformis and a coefficient of rolling friction of 0.16 between M. veneriformis–stainless steel. After calibration, simulation tests were conducted using the side plate lifting method to verify the contact parameters of the discrete elements of M. veneriformis. The results showed that the simulation angle of repose of the calibrated M. veneriformis had an error of 4% concerning the true angle, thus verifying the contact parameters of the M. veneriformis. The findings of this study can serve as a valuable reference for future research on the optimal design and simulation of the sowing, harvesting, and processing equipment of M. veneriformis. The research methodology employed can provide novel insights for research on discrete elemental parameter calibration of agricultural materials, which has not been extensively studied.