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RockyDEM is used to simulate the conveying and soil-removing device to determine its optimal structural parameters in order to solve the problem of low soil removal rate and high straw loss rate of the conveying and soil-removing device of the corn straw picking and pelletizing machinery.Single-factor and multi-factor simulation tests were conducted with soil removal rate and straw loss rate as evaluation indexes, and blade to shell clearance, sieve aperture and pitch as influencing factors.The results from the experimental the soil removal rate and the straw loss rate and simulation data from the model showed good agreement. Therefore, the procedures of this study can be used for the design and optimisation of conveying and soil-removing device.

The corrosion of steel bars in concrete has a significant impact on the durability of constructed structures. Based on the gray relational analysis (GRA) of the accelerated corrosion data and practical engineering data using MATLAB, a back propagation neural network (BPNN) model, a multivariable gray prediction model (GM (1, N)), and an optimization multivariable gray prediction model (OGM (1, N)) of steel corrosion were established by using a sequence of the key affecting factors. By comparing the prediction results of the three models, it is found that the GM (1, N) model has larger fitting and prediction errors for steel corrosion, while the OGM (1, N) model has smaller prediction errors in the accelerated corrosion data; the BPNN model offers more accurate predictions of the practical engineering data. The results show that the BPNN and OGM (1, N) models are all suitable for the prediction of steel bar corrosion in concrete structures.

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