基于局部建模方法的卧式柔性清土辊性能优化

针对基于整体建模的卧式柔性清土辊性能优化方法存在仿真成本高的问题，该研究提出一种局部预测整体的建模方法，既降低仿真计算量，同时可以对柔性清土辊进行优化设计。首先，提取柔性清土辊的最小结构特征，并基于几何相似性原理构建整体性能预测模型。其次，基于离散元法（Discreteelementmethod,DEM）与多柔性体动力学（multi-flexible-bodydynamics,MFBD）耦合仿真技术优化求解最小特征结构的最优作业性能。最后，依据预测模型估算柔性清土辊的整体性能。柔性清土辊的清土率和阻力矩与其刷片数量的线性拟合决定系数分别为0.987和0.99。基于局部建模方法和EDEM-RecurDyn耦合技术建立最小特征结构与土壤互作模型，其接触计算量仅为整体建模方法的8%左右。前进速度、安装角、轴向长度和叶片锥角对最小特征结构和刷片的作业性能影响显著，仿真优化结果分别为0.3 m/s、30°、50 mm和0°。上述条件下最小特征结构的清土率和阻力矩为36.87%、18.91 N·m，单个刷片的清土率和阻力矩为2.80%和2.78 N·m，最小特征结构的物理试验结果与仿真结果的相对误...

Optimization of the performance of the horizontal flexible soil-clearing roller using partial modeling

Grapes can be cultivated in the cold areas of northern China. The cold-proof soil clearing has been the typical operation to prevent the freezing damage under the cold climate. Among them, the flexible roller is one of the most important components for the spring soil-clearing operation in northern grapes. The operating parameters have also posed a great impact on the performance of soil clearing. The numerical simulation can normally be used to optimize the operating parameters for the flexible soil-clearing roller. However, the overall modeling is confined to the harsh requirements so far, such as the large computational volume, long computation duration, and high configuration. In this study, a partial modeling of parameters was proposed to predict the whole one, in order to significantly reduce the cost of simulation calculation. Firstly, the minimum structure feature was extracted from the flexible soil-clearing roller. A prediction model of the overall performance was then constructed using the geometric similarity. Secondly, the minimum feature model of structure-soil interaction was established for the optimal operational performance using the coupled Discrete element method (DEM), and Multi-flexible-body dynamics (MFBD). Finally, the overall performance of the flexible soil clearing-roller was estimated using the prediction model. The results showed that a strong linear correlation was found in the linear fit R2 values of 0.987, and 0.993 between the soil clearing rate and resistance torque of the flexible soil clearing-roller with the brush piece number, respectively. It infers that the linear model was used to accurately describe the relationship between the overall and partial performance. A series of finite element models (FEM) were established for the rubber sheet with the solid 10 cells and the damping ratio 0.005, while the brush wire with the solid 4 cells and damping ratio of 5×10-4, and the brush blade with the array density 90 of brush wire. The relative errors were 8.43%, and 1.52% for the simulation and physical measurements, respectively, for the minimum feature structure of the soil clearing rate and resistance torque in this case, indicating the excellent consistence with relatively small ones. Once different numbers of brush pieces were added, the maximum relative errors were 8.43%, and 10.53%, respectively, indicating the accurate and reliable model. Meanwhile, the contact calculation volume of the partial modeling was only about 8% of the overall modeling, which was effectively reduce the simulation calculation cost. Furthermore, an optimal combination was achieved, with the forward speed of 0.3m/s, the mounting angle of 30°, the axial length of 50mm, and the blade taper angle of 0°. The significant effects were also found on the operational performance of the minimum feature structure and brush piece. Specifically, the soil clearing rates of the whole and single brush piece were 36.87%, and 2.80%, respectively, whereas, the resistance torques were 18.91 and 2.78 N·m, respectively, for the minimum feature structure under the optimal condition. The relative errors were 3.74% and 10.15% between physical and simulation of the minimum feature structure under the same conditions, where the relative errors of brush piece were 10.36%, and 9.71%, indicating the accurate and reliable simulation optimization. Anyway, the soil clearing rate and resistance torque were 97.07%, and 78.68 N·m, respectively, for the flexible soil-clearing roller that estimated by the prediction model. The relative errors between the physical and the predicted were 7.84%, and 4.55%. The relative errors between the optimized by the overall modeling and the predicted were 10.66%, and 6.76%, indicating the partial modeling with the high feasibility and accuracy. The findings can also provide a new idea for the interaction modeling between the complex flexible bodies and bulk particles.