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When the outbreak of COVID-19 began, people could not go out. It was not allowed to provide agricultural machinery services in different places across regions to reduce the flow and gathering of people. Improvement of utilization efficiency of agricultural machinery resources is required through scientific scheduling of agricultural machinery. With seizing the farming season and stabilizing production as the goal, this paper studied the scientific scheduling of tractors within the scope of town and established agricultural machinery operation scheduling model with the minimization of total scheduling cost as the optimization objective. Factors such as farmland area, agricultural machinery, and farmland location information and operating time window are considered in this model to improve the accuracy of the agricultural machinery operation scheduling model. The characteristics of multiple scheduling algorithms are analyzed comprehensively. The scheduling requirements of agricultural machinery operation to ensure spring ploughing are combined to design the agricultural machinery scheduling algorithm based on the SA algorithm. With Hushu Street, Jiangning District, Nanjing City, as an example, a comparative experiment is conducted on the simulated annealing algorithm (SA) designed in this paper and the empirical algorithm and genetic algorithm (GA). The results suggest that the total cost of the scheduling scheme generated by the SA algorithm is 19,042.07 yuan lower than that by the empirical scheduling algorithm and 779.19 yuan lower than that by the genetic algorithm on average. Compared with the GA algorithm, the transfer distance, waiting cost, and delay cost of the SA algorithm are reduced by 11.6%, 100%, and 98.1% on average, indicating that the transfer distance of agricultural machinery in the scheduling scheme generated by the SA algorithm is shorter, so is the waiting and delay time. Meanwhile, it can effectively obtain the near-optimal solution that meets the time window constraint, with good convergence, stability, and adaptability. [ABSTRACT FROM AUTHOR]

Grouting reinforcement technology gradually has been widely used to repair the subgrade settlement diseases, but the current single application of discrete element software or finite element software cannot effectively simulate the grouting process. Therefore, one new method is put forward in the research of grouting based on the CFD-DEM coupling principle. And then, one typical subgrade section in the Shanghai–Nanjing intercity railway is used to simulate the grouting process and diffusion mechanism of slurry from microlevel. Based on the results of site survey, some findings are shown as follows: First, the new method is feasible which integrates the favorable aspects of discrete elements, finite elements, and boundary elements. Second, the greater the grouting pressure, the greater the influence range of grouting, and it shows six petals shape. When the grouting pressure is small, the grouting generally shows penetration or extrusion grouting, and its influence range is small. When the grouting pressure is large enough, it is characterized by splitting grouting, and the influence range of grouting is getting larger and larger. Third, the growth rates of influence range gradually increase with the increasement of grouting pressures, and the reasonable selection of grouting pressures is very important. [ABSTRACT FROM AUTHOR]