Performance optimization of gas turbine engine

Performance optimization of a gas turbine engine can be expressed in terms of minimizing fuel consumption while maintaining nominal thrust output, maximizing thrust for the same fuel consumption and minimizing turbine blade temperature. Additional control layers are used to improve engine performance. This paper presents an evolutionary approach called the StudGA as the optimization framework to design for optimal performance in terms of the three criteria above. This approach converges fast and can potentially save on computing cost. Model-based experimental results are used to illustrate this approach.