Robust optimization of subsonic airfoil considering manufacturing deviation and multi-working conditions

In order to reduce the sensitivity of compressor blade profile performance to manufacturing deviation， the multi-objective robust optimization design platform of compressor blade profile is established by integrating the two-dimensional blade parametric modeling method， reduction probabilistic model of profile deviation based on Karhunen-Loève expansion， uncertainty quantification method of polynomial chaos expansion （PCE） based on least angle regression selection （LARS）， Kriging surrogate model and NSGA-II optimization algorithm. The multi-objective robust optimization design is performed for the subsonic compressor blade profile. The uncertainty of manufacturing deviation and influence of multiple operating conditions are considered. The mean value and standard deviation of total pressure loss coefficient are minimized as the objective function， and the static pressure ratio is used as the constraint. The sensitivity of objective functions to optimization variables and the flow mechanism of performance improvement are analyzed. The results show that the performance of optimized blade profile is improved within a wide operating range， and the sensitivity to profile deviation is decreased. The maximum reductions of mean value and standard deviation of total pressure loss coefficient are 10.4% and 29.89% respectively. The mid and aft part of suction surface curve have the more obvious effect on mean value and standard deviation of total pressure loss coefficient， and the correlation coefficient is negative. The forward movement of position of maximum thickness can reduce the mean value of total pressure loss coefficient， and the increase of vertical coordinate of suction surface control point near leading edge can reduce the standard deviation of total pressure loss coefficient. The boundary layer separation of suction surface near trailing edge are the main factor for influencing the blade profile performance and sensitivity.