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针对长短叶片混流式水轮机选择不同湍流模型、各部件网格划分方案对流量、转矩、效率预测相对偏差值较大、预测精度较低问题,利用ICEM CFD划分软件对各工况(小流量、设计流量、大流量)下的水轮机全流道及其过流部件(蜗壳及导叶、转轮、尾水管)各划分出4种网格分配方案,采用收敛较快的S-A模型初步预测了水轮机的水力效率与所划分的网格规模无关,进而选择方案3分析水轮机的水力性能;选取S-A模型、标准κ-ε模型、RNGκ-ε模型、标准κ-ω模型、SSTκ-ω模型5种湍流模型计算了流量、转矩、水力效率的预测值,发现各模型预测的水力效率预测精度较高,但流量及转矩的预测精度偏低。为此,重新划分过流部件网格规模,并再划分出5种网格方案,仍采用S-A湍流模型进行初步分析,发现虽可提高流量及转矩的预测精度,但提升幅度有限;进而采用RNGκ-ε、SSTκ-ω模型、Realizableκ-ε模型、RSM模型预测流量及转矩,可进一步提高流量、转矩的预测精度,但仍低于效率的预测精度。所提出的预测方法可为水力机械设计和性能优化提供重要参考。
Different turbulence models are selected for the long-short vane Francis turbine. The grid meshing schemes of each component have a large relative deviation of flow rate, torque and efficiency prediction, and the prediction accuracy is low. ICEM CFD software is used to simulate the conditions of low- Design flows and large flow rates), four kinds of grid allocation schemes were divided into four parts: full flow path of turbine and its flow components (volute, guide vane, runner and draft tube). The SA model with faster convergence was used to predict The hydraulic efficiency of the turbine has nothing to do with the size of the grid divided, and then choose the program 3 to analyze the hydraulic performance of the hydraulic turbine. Five models of SA model, standard κ-ε model, RNGκ-ε model, standard κ-ω model and SSTκ-ω model The turbulence model calculates the predicted values of flow, torque and hydraulic efficiency. It is found that the prediction accuracy of hydraulic efficiency in each model is high, but the prediction accuracy of flow and torque is low. To this end, we re-divided the size of the flow component grid, and then divided into five kinds of grid scheme, SA turbulence model is still used for preliminary analysis and found that although the traffic and torque prediction accuracy can be improved, but the improvement is limited; and then use RNGκ-ε, SSTκ-ω model, Realizableκ-ε model and RSM model can predict the flow and torque, which can further improve the prediction accuracy of flow and torque, but still lower than the prediction accuracy of efficiency. The proposed prediction method can provide an important reference for hydraulic machinery design and performance optimization.