Automated multi-objective and multidisciplinary design optimization of a transonic turbine stage

An automated multi-objective and multidisciplinary design optimization (MDO) of a transonic turbine stage to maximize the isentropic efficiency and minimize the maximum stress of the rotor with constraints on mass flowrate and dynamic frequencies is presented in this article. The self-adaptive multi-objective differential evolution (SMODE) algorithm is studied and developed to seek Pareto solutions of the optimization, and a new constraint-handling method based on multi-objective optimization concept is applied for constraint handling. The optimization performance of the presented SMODE is demonstrated using the typical mathematical tests. By applying SMODE as an optimizer and integrating three-dimensional (3D) blade modelling method based on non-uniform B-spline, load-fitting transfer algorithm in parameter space, 3D Navier–Stokes solution technique, and finite element analysis method as well, seven Pareto solutions are obtained. Two Pareto solutions are analysed in detail. One is the highest isentropic efficiency individual, while the other is a compromise between efficiency and mechanical stress in the blade. The aerodynamic performance and strength characteristics of the optimized turbine stage are significantly improved. The analysis results indicate that the presented multi-objective and MDO method has a potential in the optimization of blade performance and can be applied as a promising method for the optimization design of axial turbomachinery blades

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