A set of suitable parameter values is crucial in discrete element method (DEM) simulations. As a non-spherical particle, the coefficients of rolling friction between maize seed particles and between the seed particles and the boundary are hard to measure directly and must be obtained by calibration. In this paper, taking three representative maize varieties as research objects, the necessity for the accurate calibration of the coefficients of rolling friction between seed particles and between seed particles and boundaries is investigated. Subsequently, by studying the sensitivity of the coefficients of rolling friction between seed particles and between seed particles and the boundary to the angle of repose test, the methods used to calibrate the coefficients of rolling friction between seed particles and between the particles and the boundary are determined. It can be seen from the results that the coefficients of rolling friction between the seed particles and between the seed particles and the boundary have a significant influence on the test results, so these two parameters must be accurately calibrated. Additionally, the coefficient of rolling friction between seed particles and the boundary has no effect on the piling angle, but the piling angle is highly sensitive to the coefficient of rolling friction between seed particles. By comparing the simulation results and the experimental results in the lifting cylinder and “self-flow screening” tests, the calibrated seed parameters were found to be accurate and valid.

This paper takes a local drum-type corn thresher as an example. In order to make the threshing principle transform to the plate-tooth type, the width of the spike-tooth threshing component is increased gradually, and three threshing components of different shape and size are selected as the research objects. Based on the preliminary experimental research, the corn threshing process is simulation analyzed using the self-developed corn threshing process analysis software. The effects of the width of the threshing component on the corn ears threshing rate and kernel damage rate under different rates of drum rotation were studied from a macroscopic perspective. The results show that with the increase of drum rotation rate, both the corn ear threshing rate and kernel damage rate increase; with the increase of threshing component width, the threshing rate increases and the damage rate decreases; and when the component width is too large, the stacking between adjacent components has an impact on the threshing performance. The effects of threshing component width on the amount of kernel threshing and the total compressive force during the simulation time were investigated from microscopic perspective at different rates of drum rotation, and the results show that the microscopic analysis is consistent with the macroscopic analysis. Therefore, the optimization of the structural parameters and operating parameters of the threshing component was achieved. When the width of the threshing component was 25 mm and the roller speed was 187.50 rpm, the threshing performance was optimal, with a 98.04% corn ears threshing rate and a 2.56% kernel damage rate. This paper verifies the practical applicability of the corn threshing process analysis software and provides a reference for the optimal design of threshing devices.

Current corn kernel-cob bonding mechanics models (LSD models) uniformly consider the bonding force changes during the maize threshing operation as an elastic change, resulting in computational errors of up to 10% or more in discrete element simulations. Due to the inability to perform high-precision discrete element simulation of the mechanics characteristics during the corn threshing operation, the core operating parameters of the corn thresher (rotation speed of the threshing component) rely mainly on empirical settings, resulting in a consistent difficulty in exceeding 85% of the corn ear threshing rate. In this paper, by testing the mechanics characteristics of corn kernels, the bonding force is found to have both elastic and plastic changes during the threshing process. An elastic–plastic (EP) damping model of the corn kernel–cob bonding force was established by introducing a bonding restitution coefficient e to achieve an integrated consideration of the two changes. By testing the relationship between the properties of the corn ear itself and the model parameters, the pattern of the effect of the corn ear moisture content and the loading direction of the ear by force on the EP model parameters was found. By establishing a model of the relationship between the corn cob’s own properties and the model parameters, the EP model parameter values can be determined by simply determining the moisture content of the ear. In this paper, the EP model was established and the high-precision simulation and analysis of the process of bonding force variation between corn kernel and cob is realized on the self-developed AgriDEM software. At the meantime, the optimal values of the threshing component rotation speed under different conditions of moisture content of corn ear were obtained by establishing an optimization model of threshing component rotation speed. The test results showed that the corn ear threshing rate could reach more than 92.40% after adopting the optimized speed value of the threshing component in this paper. Meanwhile, the test results showed that the discrete element simulation results based on the EP model did not significantly differ from the measured results of the thresher. Compared with the most widely used LSD model, the EP model can reduce the computational error by 3.35% to 6.05%.

To solve the poor universality in the existing modelling approaches of soybean particles, we proposed a soybean particle modelling approach by combining five, nine, and 13 balls. The soybean seeds from three varieties (Suinong42, Jidou17, and Zhongdou39 with a sphericity of 94.78%, 86.86%, and 80.6%, respectively) are chosen as the study objects. By the comparisons between the simulation results and the test results in the “self-flow screening” and “piling angle” tests, it is concluded that the soybean particle modelling approach we presented in this paper is a universal modelling approach appropriate for soybean particles with different sphericities. The five-ball model is appropriate for the soybean particles with high sphericity, and the nine- or 13-ball models are applicable to those with low sphericity. The soybean particle modelling approach we presented is also compared with the ellipsoidal equation modelling approach for soybean particles and with the modelling approaches presented by other researchers. From an overall perspective, the soybean particle modelling approach we presented is better than the ellipsoidal equation modelling approach and those modelling approaches presented by other researchers. Additionally, it is shown that the multiple contacts issue in the multi-ball model has a little influence on the simulation results of soybean particle models. The study in this paper provides a new modelling approach for soybean particles in the DEM simulation of the contacts between soybean particles and the related machines.

The high energy consumption and low crushing length qualification rate of traditional straw returning machines in the main maize-growing regions of northeast China make it difficult to promote straw returning operations in the region. The primnoa locust mouthpart is extremely efficient in cutting maize rootstocks. In this paper, it was found that there are significant differences between the primnoa locust mouthpart and the conventional machine, these exist mainly in the cutting edge structure and cutting motion. Thus, this paper develops a coupled bionic design for structural and kinematic coupling elements to develop a bionic straw returning machine. This paper found that the operating performance of the bionic straw returning machine was mainly affected by the blade rotation radius and the output rotation speed of the drive mechanism through DEM (discrete element method) simulation, and the optimal combination of the two parameters was 248 mm rotation radius and 930 r/min output rotation speed. Finally, this paper finds that the most obvious operational performance difference of the bionic straw returning machine compared with the traditional straw returning machine is that it can reduce the cutting power consumption by 9.4–11.7% and improve the crushing length qualification rate by 10.4–14.7% through the operational performance comparison test. Based on the above findings, this paper suggests that in future research and development of straw returning machines, more attention can be focused on finding suitable bionic prototypes and improving bionic design methods.

An appropriate contact mechanics model and parameters are key to achieving accurate results in discrete element analyzis. This is necessary to predict the process of contact collision between the soil and maize seed during deposition. In this paper, the contact process between maize seed and soil is analyzed using the maize seed variety (Liangyu 99) and maize-sowing field soil (with three different moisture contents) as research objects. Based on this, the contact process between maize seeds and soil has been analyzed, on the basis of which a mechanical model suitable for simulating the contact process between maize seeds and soil has been explored, and the selection of parameters between heterogeneous particles (maize seed and soil particles) has been investigated. The results showed that adhesion forces have a significant effect on the collision process between seed and soil particles. While the presence of tangential adhesion force can be replaced by increasing the static and rolling friction coefficients, the normal adhesion force cannot be compensated in this way. The Edinburgh Elasto-Plastic Adhesive (EEPA) model is selected in this paper to describe the contact between seed and soil particles. The significance of the input parameters in the EEPA model is investigated using the Plackett–Burman test. The parameters between soil and seed particles are optimized using the central composite design, and the optimal parameter combinations are obtained. The relative error between the simulation and test result of the slope test for the three soil moisture contents is within 5.4%, validating the accuracy of the calibrated parameters.