Application of genetic algorithm in exergy and sustainability: A case of aero-gas turbine engine at cruise phase

As sustainability, increasing of fuel and energy efficiency has become a greater concern in aircraft design and fleet operation for two decades. To meet this need, a new methodology is being developed here that proposes the use of optimization for indexing the sustainability throughout flight phases of the aircraft and its power system. In this study, off-design modeling of several exergetic parameters for the turbofan engine is conducted by using genetic algorithm at cruise phase. In this context, exergetic sustainability parameters such as exergy efficiency, wasted exergy ratio, exergy destruction factor, environmental effect factor and exergetic sustainability index are calculated for the aircraft engine. After this process, linear modeling of exergetic indexes, depending on Mach (0.7-0.9) and altitude (9-11 km) ranges is performed. The results highlight that the linear modeling of exergetic parameters with the genetic algorithm (GA) enhances accuracy of the model compared to the least square method (LSM). Modeling of exergy efficiency for the turbofan is achieved with R = 0.9974 by LSM whereas it is obtained with R = 0.9999 by GA at altitude of 11 km. Finally, modeling of exergetic metrics for turbofan engine by using parametric flight data could enable so as to determine optimum cruise flight conditions in terms of both engine performance and environmental sustainability. (c) 2021 Elsevier Ltd. All rights reserved.