In this research, numerical optimization of the rear part of a gas turbine, consisting of a single stage axial turbine is carried out. Automated aerodynamic shape optimization is performed by coupling a CFD flow simulation code with the Genetic Algorithm. An effective multi-point optimization method to improve efficiency and/or pressure ratio of the axial turbine is performed. Some variations of optimization parameters such as lean and sweep angels of stator and rotor blades are accomplished. Furthermore, during the optimization process, three-dimensional and turbulent flow field is numerically investigated using a compressible Navier-Stokes solver. The gas turbine experimental investigations are used for choosing optimization points, specifying the boundary conditions and validation of the simulations. Two operating speeds of the gas turbine are selected for the optimization. Using verified numerical simulation models and the genetic algorithm, the effects of stator and rotor lean and sweep angles on the turbine performance are studied. The present optimization method successfully obtains a result that improves 1.31% and 1.17% in the turbine stage total-to-total efficiency in its design and off-design speeds, respectively. The modified turbine mass parameter at choke condition increases 2.40%.

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