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Gas turbine engines are highly efficient and powerful because of theirhigh-pressure turbines (HPTs). Furthermore, stationary blades shape and preparehigh-pressure gas for efficient utilization by moving blades. Consequently,optimizing the geometric features of both stationary and moving blades duringthe first and second stages of HPT is necessary. By considering stagger, inlet,and outlet angles of the first and second stages of blades as design variablesand polytropic efficiency as an objective, this study examines HPT performance.The performance characteristics of the turbine are examined using ComputationalFluid Dynamics (CFD). To model the objective functions of the design variables,the Design of Experiments (DOE) method is employed. A Genetic Algorithm (GA)optimizes torque, power, and polytropic efficiency. Optimization providesvaluable insights into optimal design principles. As shown by the simulationresults, stagger, inlet, and outlet angles affect turbine performance. ThroughGA optimization, torque, power, and polytropic efficiency are improved by 8.4%,0.69%, and 1.2%, respectively. As a result of these improvements, theoptimization approach has been demonstrated to be effective in optimizingturbine performance. Upon examining the recommended design points, it becomesclear that stagger, inlet, and outlet angles of blades have a greater impact onperformance than others.

Numerical Simulation and Aerodynamic Optimization of Two-Stage Axial High-Pressure Turbine Blades