基于整机试验数据辨识的雷诺数对涡扇发动机的性能影响

为了研究雷诺数对涡扇发动机性能的影响并提升稳态性能模型在工作包线内的计算精度，提出了一种基于整机试验数据辨识的计算分析方法。选取用于气路分析的测量参数，提升辨识算法的收敛性和计算结果的有效性；结合非线性气路分析算法辨识计算出各试验点的部件性能修正因子，统计分析雷诺数和各部件性能修正因子的变化关系，定量得到雷诺数对发动机各部件性能的影响程度；修正基线稳态性能模型，并对计算精度进行验证对比。结果表明:对比试验结果，修正后的稳态性能模型各参数计算偏差不大于2.5%。对比基线稳态性能模型各参数计算结果，计算精度平均提升2.3%，最大提升9.2%。 

Reynolds number effects on performance of turbofan based on whole engine test data identification

In order to investigate Reynolds number effects on the performance of turbofan and improve state performance model calculation accuracy in flight envelope, a computational analysis method based on whole engine test data identification was presented. Identification algorithm convergence and result validity were improved through measurement parameters selection for gas path analysis. Component performance scale factor for each test point was identified by non-linear gas path analysis method. Statistical analysis of the relationship between Reynolds Number and component performance scale factor was performed, and the performance change of each component affected by Reynolds Number was quantitatively obtained. Baseline steady state performance model was modified and calculation accuracy was compared and verified. Compared with test data, modified steady state performance model calculation error was not more than 2.5%. Compared with baseline steady state performance model calculation result for each parameter, the average calculation accuracy was improved 2.3%, and the maximal calculation accuracy was improved 9.2%.