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This paper presents an aerodynamic optimum design method for transonic turbine cascades based on the Genetic Algorithms coupled to the inviscid flow Euler solver and the boundary-layer calculation.The Genetic Algorithms control the evolution of a population of cascades towards an optimum design.The fitness value of each string is evaluated using the flow solver. The design procedur6 has been developed and the behavior of the genetic algorithms has been tested. The objective functions of the design examples are the minimum mean-square deviation between the aimed pressure and computed pressure and the minimum amount of user expertise.
This paper presents an aerodynamic optimum design method for transonic turbine cascades based on the Genetic Algorithms coupled to the inviscid flow Euler solver and the boundary-layer calculation. The Genetic Algorithms control the evolution of a population of cascades towards an optimum design. The fitness value The objective functions of the design examples are the minimum mean-square deviation between the aimed pressure and computed pressure and the minimum amount of user expertise.