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A fast numerical method for flow analysis and blade design in centrifugal pump impellers

机译:离心泵叶轮流动分析和叶片设计的快速数值方法

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摘要

A numerical methodology is developed to simulate the turbulent flow in a 2-dimensional centrifugal pump impeller and to compute the characteristic performance curves of the entire pump. The flow domain is discretized with a polar, Cartesian mesh and the Reynolds-averaged Navier-Stokes (RANS) equations are solved with the control volume approach and the k-s turbulence model. Advanced numerical techniques for adaptive grid refinement and for treatment of grid cells that do not fit the irregular boundaries are implemented in order to achieve a fully automated grid construction for any impeller design, as well as to produce results of adequate precision and accuracy. After estimating the additional hydraulic losses in the casing and the inlet and outlet sections of the pump, the performance of the pump can be predicted using the numerical results from the impeller section only. The regulation of various energy loss coefficients involved in the model is carried out for a commercial pump, for which there are available measurements. The predicted overall efficiency curve of the pump was found to agree very well with the corresponding experimental data. Finally, a numerical optimization algorithm based on the unconstrained gradient approach is developed and combined with the evaluation software in order to find the impeller geometry that maximizes the pump efficiency, using as free design variables the blade angles at the leading and the trailing edge. The results verified that the optimization process can converge very fast and to reasonable optimal values.
机译:开发了一种数值方法来模拟二维离心泵叶轮中的湍流并计算整个泵的特性曲线。用极坐标笛卡尔网格离散流域,并使用控制体积方法和k-s湍流模型求解雷诺平均Navier-Stokes(RANS)方程。实施了先进的数值技术,用于自适应网格细化和用于处理不适合不规则边界的网格单元,以实现针对任何叶轮设计的全自动网格构造,并产生足够的精度和准确性。在估算了泵的壳体以及进口和出口部分的额外液压损失后,仅可以使用叶轮部分的数值结果来预测泵的性能。模型中涉及的各种能量损失系数的调节是针对商用泵进行的,对此有可用的测量方法。发现泵的预测总体效率曲线与相应的实验数据非常吻合。最后,开发了一种基于无约束梯度方法的数值优化算法,并将其与评估软件相结合,以使用前缘和后缘的叶片角度作为自由设计变量,找到使泵效率最大化的叶轮几何形状。结果证明,优化过程可以快速收敛并达到合理的最优值。

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