| Summary: | Turbo-machinery design is clearly about making many decisions often under uncertainty and with multiple conflicting objectives. In this work, a computational tool has been developed to assist in the preliminary design optimization of supersonic turbines with application on turbopump rocket engines. It was proposed an evolutive approach based on genetic algorithm to automatize the process of selecting values, based on hands-on experience, for decision variables and fulfill simultaneously decisive compromises faced by the designer. At design point, exploring multiple optima solutions, the tool allows to fast estimate in a robust and accurate manner, performance, main dimensions, mass of rotor-wheel and the lower possible flow rate of the turbine. Out of this point, performance maps can be calculated varying rotational speed and pressure ratio. Because, it is involved by many objectives, a Pareto-optimum set is found. The search ends when the relation power-to-weight converges. The power-to-weight ratio characterizes a good option to relate performance and weight among distinct turbopump turbines. The empirical loss models adopted as well as the recommended values in the selection of decision variables were obtained in the Russian literature. To demonstrate the functionalities of tool, the single-stage of the Soviet RD109 rocket turbine was redesigned. The results were validated from those found in the engine';s atlas of construction and also, by a statistical method of calculation defined from an experimental study that estimates the maximum turbine efficiency.
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