Design of axial turbines, especially LP turbines, poses difficult tradeoffs between requirements of aerodynamic design and structural limitations. In this paper, a methodology is proposed for 3D multi-objective design of axial turbine blades in which a 3D inverse design method is coupled with a multi-objective genetic algorithm. By parameterizing the blade using blade loading parameters, spanwise work distribution and maximum thickness, a large part of the design space can be explored with very few design parameters. Furthermore, the inverse method not only computes the blade shape but also provides accurate 3D inviscid flow information. In the simple multi-disciplinary approach proposed here the different losses in axial turbines such as endwall losses, tip leakage losses and an indication of flow separation are related through well known correlations to the blade surface velocities predicted by the inverse design method. In addition, geometrical features such as throat area, lean angles and airfoil cross sectional area are computed from the blade shape employed during the optimization. Also, centrifugal stresses and bending stresses are related to the blade geometry. The methodology is then applied to the redesign of an LP turbine rotor with the aim of reducing the maximum stresses while maintaining the performance of the rotor. The results are confirmed by using the commercial CFX CFD (Computational Fluid Dynamics) code and Ansys FEA (Finite Element Analysis) codes.

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