不同湍流模型在轴流泵性能预测中的应用  

Application of different turbulence models for predicting performance of axial flow pump

作　　者：张德胜[1] 施卫东[1] 张华[1] 姚捷[1] 关醒凡[1] 

机构地区：[1]江苏大学流体机械工程技术研究中心,镇江212013

出　　处：《农业工程学报》2012年第1期66-71,I0004,共7页Transactions of the Chinese Society of Agricultural Engineering

基　　金：国家自然科学基金(51109093;51079063);江苏省自然科学基金(BK2011503);国家博士后科学基金(2011M500117);东南大学水声信号处理教育部重点实验室开放研究基金(UASP1006);江苏大学高级人才启动基金(11JDG038);江苏省博士后基金(1101019B)

摘　　要：为了评价不同湍流模型在轴流泵性能预测中的精度,该文以南水北调工程轴流泵模型作为研究对象,分别选取了3种湍流模型标准k-ε湍流模型(standard k-ε)、重正化群k-ε湍流模型(renormalization group k-ε,RNG)和雷诺应力模型(reynolds stress model,RSM),基于SIMPLE算法(semi-implicit method for pressure-linked equations)和结构化网格,进行了轴流泵性能预测和全流场数值模拟,并以水利部天津同台测试的试验结果作为基准对预测扬程和效率进行了误差分析。研究结果表明,网格密度对模拟结果具有较大影响,较疏的网格导致性能预测精度降低,在大流量和小流量工况下预测的扬程和效率误差将达到3%以上;在最优工况下,Standard k-ε、RNG k-ε和RSM湍流模型的扬程预测误差分别为0.97%、1.12%和1.24%,效率预测误差分别为2.93%、2.49%和2.97%,可满足工程应用要求;但在非设计工况下,由于二次回流、空化等复杂流动的存在,内部流场复杂,3种湍流模型的扬程最大预测误差范围为9.40%～14.30%,效率最大预测误差范围为4.48%～8.30%。该结论将为轴流泵性能预测的可靠性提供依据。In order to evaluate the performance prediction accuracy of axial flow pump under different turbulence models, the axial flow model used in South-to-North Water Diversion Project was study object, the standard k-ε、RNG k-ε（renormalization group k-ε）and RSM（reynolds stress model） are used to predict the performance of axial flow pump and numerically simulate its flow field based on SIMPLE（semi-implicit method for pressure-linked equations） algorithm and structured hexahedral mesh. The simulated head and efficiency error compared with experimental results which are tested by ministry of water resources in Tianjin were analyzed. The results showed that simulation results were affected by the mesh density, and the head and efficiency prediction errors were increased by the sparse grid in the large flow rata and small flow rata conditions, which would reach 3% or more; Predictive errors of the head for Standard k-ε, RNG k-ε and RSM turbulence model were 0.97%, 1.12% and 1.24% respectively, and the efficiency of errors were 2.93%, 2.49% and 2.97% under the optimal conditions, which could meet the needs of engineering applications. However, the flow field is complex because the secondary flow and cavitations exist under off-design conditions. The head maximum predictive error range of three turbulence models was 9.40%-14.30%, the efficiency was 4.48%-8.30%. The conclusions in this paper will provide a reliable performance prediction data and practice for the axial flow pump.

关 键 词：轴流 泵 湍流模型 误差分析 性能预测 网格 

分 类 号：TH312[机械工程—机械制造及自动化]