Abstract:The angle of repose (AoR) is one of the most important macroscopic parameters in characterizing the behavior of vermicomposting nursery substrate. It is strongly depended on the material properties, such as moisture content, particle density, sliding and rolling frictions of particles, particle size and shape. A simulation and experimental study was presented to determine the AoR of vermicomposting nursery substrate under different moisture contents, and the other parameters such as sliding and rolling frictions were investigated. The simulation model was performed by discrete element method (DEM). An AoR measuring instrument was designed. The outline of the accumulation body was obtained by digital image analysis (DIA) method, and fitted with the Gaussian distribution formula to fit the AoR. The Plackett-Burman test was used to select the experimental factors with significant effect on the results. Based on the JKR contact model, the coefficient of static friction between the particles, the coefficient of rolling friction between the particles and the surface energy of JKR were represented from the parameters related to vermicomposting nursery substrate particles. The Box-Behnken test was carried out to obtain the regression model between the AoR and the significant parameters. Quadratic polynomial regression model between AoR and the three significant parameters was established. The comparison between the more common linear fitting model and the exponential fitting model proposed was carried out. The experimental results showed that the model can predict the vermicomposting nursery substrate parameters based on the AoR. The simulation results were compared with the experimental measurements, and the results of AoR agreed with the actual results, where the difference was 1.53% and 0.22%, respectively. Also, the exponential fitting model was more accurate. Finally, the research results can provide a reference for the determination of AoR of other bulk materials and provide a way to derive other unpredictable parameters by measuring readily measured parameters such as moisture content.
