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The gap between concave grid and drum, the threshing gap, is one of the important operating parameters that affects the performance of threshing devices. The different methods currently adopted on combine harvesters to adjust both the drum and the concave, results in concentric and non-concentric threshing gaps that have different influence on e threshing performance. The threshing process is complex, therefore, in order to analyse the influence of the threshing gap on performance, flexible rice straw models were built using the discrete element method to simulate the threshing processes of the two adjustment methods. Their respective movements, separation status and the distribution of the mixture of the threshed output were examined. Simulation results indicated that over the same time, drum adjustment produced better material separation and transportation capabilities and more evenly distributed output mixture in the reception box, compared with the concave adjustment. A threshing experiment on a combine harvester was performed in order to verify the simulation result and the output mixture distribution status was found to be consistent with the results of the simulations. The experimental results showed that threshing was more effectively improved by changing the threshing drum diameter although the threshing gap was more complicated to adjust.

To predict the cleaning performance of rice combine harvesters, numerical simulations of the air-and-screen cleaning unit using coupled computational fluid dynamics and discrete element method were used to study the gas–solid two-phase flow behaviour of the threshed mixture. The calculation methods investigated the centroid velocities of three particle classes: grains, stems and light impurities, and the degree of dispersion of all particles. It was found that the centroid velocity of the grain particles was the least affected by different working conditions at the same cleaning time, and the movement of grain particles did not reflect the varying cleaning performances. The degree of dispersion of all particles at each working condition reached a relatively stable state with cleaning times 1.3 s–2.0 s, and this period was taken as the analysis period. Cleaning performance experiments were carried out on the developed air-and-screen cleaning test-bed under corresponding conditions. The mathematical relationships between the centroid velocity of each particle class, the degrees of dispersion of all particles and the cleaning performance were studied. After comparison and analysis, it was concluded that the prediction model between the degree of dispersion of all particles and the cleaning loss ratio had an error less than 9.4%. The centroid velocity of short stem particles in X direction and the grain impurity ratio had an error less than 11.7%. This simulation method therefore had relatively good accuracy and can be used make up for the shortcomings caused by the seasonality of field testing and also save costs in designing cleaning units.