Numerical study on parameter optimization of the film hole with thermal barrier coating based on RSM
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摘要:
为解决有涂层时多种因素导致气膜冷效优化计算成本增大的问题,通过Box-Behnken方法合理设计3个吹风比(0.5、1.0和1.5)下,气膜孔流向倾角、长径比和涂层厚度3种参数的耦合模型,利用Realizable
k-ε 湍流模型进行数值模拟,将模拟结果通过响应面分析法(RSM)得到响应方程,最终通过响应方程预测最优参数。结果表明:孔倾角和涂层厚度为影响有涂层(TBC)气膜孔冷效的主要因素,长径比为影响冷效的次要因素。通过响应方程预测能达到最优气膜冷效时的模型,结果显示优化模型在所研究吹风比范围内气膜冷效相对于参考提升了55.45%~90.95%,响应方程的预测误差范围为2.71%~13.42%,具有较高的准确性。Abstract:In order to solve the problem that many factors may lead to the increase of calculation cost of optimizing air film cooling efficiency, a coupling model of flow angle, length-diameter ratio and coating thickness at three blowing ratios (0.5, 1.0 and 1.5) was reasonably designed by Box-Behnken design method. Realizable
k -ε turbulence model was used for numerical simulation. Response Surface Methodology (RSM) was used to analyze the simulation results to obtain the response equation, finally the optimal parameters were predicted by the regression equation. Researches showed that flow angle and coating thickness are the main factors affecting the cooling efficiency of film holes with thermal barrier coating (TBC), and the length-diameter is the secondary factor affecting the cooling efficiency. The response equation was used to predict the optimization model with best film cooling efficiency. Within the studied blowing ratio range, the results showed that the film cooling efficiency of the optimized model was 55.45%−90.95% higher than that of the reference, and the prediction error range of the response equation was 2.71%−13.42% with higher accuracy. -
表 1 BBD方法设计的实验工况
Table 1. BBD method design of experimental conditions
工况 孔倾角/(°) 长径比 涂层厚度/mm 参考 45 1.75 0.325 Case 1 60 4.375 0.5 Case 2 45 7 0.15 Case 3 45 4.375 0.325 Case 4 30 4.375 0.15 Case 5 45 1.75 0.15 Case 6 60 1.75 0.325 Case 7 45 4.375 0.325 Case 8 45 1.75 0.5 Case 9 60 7 0.325 Case 10 30 1.75 0.325 Case 11 60 4.375 0.15 Case 12 30 4.375 0.5 Case 13 45 7 0.5 Case 14 30 7 0.325 Case 15 45 4.375 0.325 表 2 各实验工况下游面平均气膜冷效
Table 2. Surface average film cooling efficiency of each experimental condition
工况 响应值ηave M=0.5 M=1.0 M=1.5 参考 0.0384 0.0268 0.0258 Case 1 0.0161 0.0056 0.0044 Case 2 0.0591 0.0337 0.0299 Case 3 0.0324 0.0274 0.0248 Case 4 0.0700 0.0429 0.0371 Case 5 0.0617 0.0335 0.0303 Case 6 0.0273 0.0219 0.0184 Case 7 0.0324 0.0273 0.0248 Case 8 0.0265 0.0218 0.0180 Case 9 0.0234 0.0223 0.0164 Case 10 0.0669 0.0410 0.0355 Case 11 0.0498 0.0286 0.0255 Case 12 0.0529 0.0384 0.0329 Case 13 0.0288 0.0297 0.0209 Case 14 0.0506 0.0344 0.0359 Case 15 0.0324 0.0273 0.0248 表 3 M=0.5时孔出口下游面平均气膜冷效方差分析
Table 3. Variance analysis of surface average film cooling efficiency at the downstream of hole outlet when M=0.5
方差来源 平方和 自由度 均方 P值 模型 4174.74 9 463.86 0.0011 A(角度) 1914.47 1 1914.47 0.0001 B(长径比) 52.43 1 52.43 0.147 C(厚度) 1691.3 1 1691.3 0.0002 AB 38.35 1 38.35 0.2024 AC 69.1 1 69.1 0.1061 BC 5.88 1 5.88 0.5908 A2 152.62 1 152.62 0.0328 B2 39.05 1 39.05 0.1989 C2 261.08 1 261.08 0.0123 残差 89.15 5 17.83 失拟项 89.15 3 29.72 < 0.0001 纯误差 1.67$ \times $10−7 2 8.33$ \times $10−8 总和 4263.88 14 表 4 M=1.0时孔出口下游面平均气膜冷效方差分析
Table 4. Variance analysis of surface average film cooling efficiency at the downstream of hole outlet when M=1.0
方差来源 平方和 自由度 均方 P值 模型 1132.22 6 188.7 0.0005 A(角度) 787.11 1 787.11 <0.0001 B(长径比) 0.4217 1 0.4217 0.8558 C(厚度) 242.45 1 242.45 0.002 AB 11.86 1 11.86 0.3485 AC 75.6 1 75.6 0.0361 BC 14.77 1 14.77 0.2988 残差 95.71 8 11.96 失拟项 95.71 6 15.95 < 0.0001 纯误差 6.67$ \times $10−9 2 3.33$ \times $10−9 总和 1227.93 14 表 5 M=1.5时孔出口下游面平均气膜冷效方差分析
Table 5. Variance analysis of surface average film cooling efficiency at the downstream of hole outlet when M=1.5
方差来源 平方和 自由度 均方 P值 模型 1133.18 6 188.86 < 0.0001 A(角度) 777.51 1 777.51 < 0.0001 A (长径比) 0.1162 1 0.1162 0.8265 A (厚度) 295.14 1 295.14 < 0.0001 A 1.47 1 1.47 0.4439 AC 56.19 1 56.19 0.0011 BC 2.76 1 2.76 0.3018 残差 18.13 8 2.27 失拟项 18.13 6 3.02 < 0.0001 纯误差 1.87$ \times $10−7 2 9.33$ \times $10−8 总和 1151.31 14 表 6 RSM方法的优化参数与预测值
Table 6. Optimized parameters and predicted values with RSM method
吹风比 孔倾角/(°) 长径比 涂层厚度/mm 预测响应值ηave M=0.5 30 1.75 0.15 0.0832 M=1.0 30 1.75 0.15 0.0436 M=1.5 30 1.753 0.15 0.0377 表 7 优化结果分析
Table 7. Analysis of optimization results
吹风比 参考模型
冷效值优化模型响应
方程预测值优化模型
计算结果值相对于参考值
的提升/%预测误差/% M=0.5 0.0377 0.0832 0.0720 90.95 13.42 M=1.0 0.0261 0.0436 0.0435 66.64 2.71 M=1.5 0.0251 0.0377 0.0387 54.45 2.73 -
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