Optimization is uprising technology in the engineering field, which enhance the performance of mechanical components. Likewise, upcoming turbomachinery designs need to be more efficient, cost-effective and easy manufacturing. Many optimization techniques have implemented for the development of efficient turbomachines. In this study, the optimization has mostly confined to the stay vane of reaction turbine like Francis, Pump Turbine etc. Stay vanes are mainly used to direct the flow towards guide vane and runner in the reaction type turbine (Francis, Pump Turbine). The three-dimensional flow field from the spiral casing is highly distorted, which causes secondary flow. However, the uniform flow field has maintained by stay vane. Due to steady flow field from stay vane, the performance of the runner has improved. Therefore, the better design of stay vane has been required for the improvement of the flow field around the runner passage. The design parameters of the stay vane are vane angle distribution and thickness distribution from leading edge to trailing edge. The vane angle distribution controls the stability of flow field direction and momentum towards the runner. Similarly, the thickness distribution will maintain the profile of the stay vane. The optimization of stay vane has improved turbine efficiency, flow uniformity, and pressure loss. The multi-objective genetic algorithm (MOGA) was selected for the optimization of stay vane because it satisfies all the objective functions without being dominated by any specific solution. MOGA is a more realistic approach to optimization. The validation test of performance is conducted to compare the result of experimental and numerical methods. The optimized stay vane has improved the flow uniformity around the stay vane.

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