A multi-objective, reliability-based design optimization technique of a compressor blade is proposed using response surface methods and genetic algorithms. The design objectives are to maximize the stage pressure ratio and to minimize the weight of the NASA rotor67 transonic blade, while satisfying both aerodynamic constraint and structural reliability constraint. Thirty two deterministic design variables are used to define the shape of the blade, while two random variables are used to

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... ize the uncertainties in material properties. Reliability analysis is performed using the second-order response surface and Monte Carlo simulation. The probabilistic sufficiency factor, which is superior to the probability of failure and safety factor in terms of accuracy in the regions of low probability of failure when calculated using Monte Carlo simulation, is used as an alternative measure of safety in reliability-based design optimization. Quadratic design response surfaces are utilized to filter the noise from the Monte Carlo simulation and also facilitate the multidisciplinary design optimization. The genetic algorithm is employed to find the Pareto-optimal solutions. To expedite the convergence and find a well-converged solution, we also use a local search. Numerical results show that with this proposed approach we * Senior Researcher, Member AIAA † Assistant Professor, Member AIAA