涡轮叶片冷却效果影响因素交互效应分析与试验研究

Analysis and Experimental Research on Interaction Effect of Influencing Factors of Turbine Blade Cooling Effectiveness

关键词:  交互效应  正交试验设计  响应面分析  冷却效果试验  涡轮叶片

Key words:  Interaction effect  Orthogonal test design  Response surface analysis methodology  Cooling effectiveness test  Turbine blade

摘要:

为研究涡轮叶片冷却效果试验中常见因素变量（质量流量比、温度比及燃气雷诺数）间的交互作用对冷却效果响应变量的影响，采用正交试验设计方案结合试验数据响应面分析方法，对各因素变量的主效应及交互效应进行了分析。结果表明：各因素的主效应对冷却效果的影响程度最大，质量流量比与温度比的交互效应影响程度其次，温度比与燃气雷诺数及质量流量比与燃气雷诺数呈现出较弱的交互效应。拟合回归了带有交互作用项的冷却效果线性化经验公式，给出了因素变量空间内冷却效果响应变量的最大值（约为0.397），95%置信区间为［0.351，0.449］，此时因素变量组合为温度比1.59，质量流量比0.039，燃气雷诺数348000。对拟合回归结果进行了检验，两个状态点的检验回归精度均不大于3%。

Abstract:

In order to study the effects of the interaction between the common factor variables （mass flow ratio， temperature ratio and gas Reynolds number） in the cooling effectiveness test of turbine blade on the response variable， an orthogonal test design scheme combined with response surface analysis methodology was carried out with the main effects and interaction effects analyzed. The results show that the main effects of each factor have the greatest influence on the cooling effectiveness， and the interaction effect between the mass flow ratio and the temperature ratio is the second. The temperature ratio with the gas Reynolds number and the mass flow ratio with the gas Reynolds number show weaker interaction effects. At the same time， the regression equation of the cooling effectiveness linearization with interaction terms is fitted， and the maximum value of the cooling effectiveness response variable in the factor variable space is given （about 0.397）. 95% confidence interval is ［0.351， 0.449］. At this time， the temperature ratio is 1.59， with the mass flow ratio 0.039， the Reynolds number 348000. Finally， the fitting regression results are tested， and the test regression accuracy of two status points is less than 3%.