  Gas turbine engines are highly efficient and powerful because of their
high-pressure turbines (HPTs). Furthermore, stationary blades shape and prepare
high-pressure gas for efficient utilization by moving blades. Consequently,
optimizing the geometric features of both stationary and moving blades during
the 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 variables
and polytropic efficiency as an objective, this study examines HPT performance.
The performance characteristics of the turbine are examined using Computational
Fluid 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 provides
valuable insights into optimal design principles. As shown by the simulation
results, stagger, inlet, and outlet angles affect turbine performance. Through
GA optimization, torque, power, and polytropic efficiency are improved by 8.4%,
0.69%, and 1.2%, respectively. As a result of these improvements, the
optimization approach has been demonstrated to be effective in optimizing
turbine performance. Upon examining the recommended design points, it becomes
clear that stagger, inlet, and outlet angles of blades have a greater impact on
performance than others.
