Performance Optimization of a Heavy Class Helicopter Engine Installation Using Genetic Algorithms Coupled With CFD Simulations

Aerodynamic design and optimization of engine installation is a pivotal part of the helicopter design process. To this purpose, an adaptive problem-independent and reliable optimization methodology would be particularly valuable for accomplishment of such goal. The application of advanced evolutionary algorithms coupled with CFD solvers for the accurate flow solution of validated numerical models represents a very powerful tool for the parametric design and optimization of engine installation components. Within the JTI Clean Sky FP7 project “HeavyCopter” the consortium constituted by the University of Padova (UNIPD) and the spin-off company HIT09 developed an automatic optimization loop based on an in-house genetic algorithm called GeDEA, and applied it to engine installation design of a heavy-class helicopter. This paper illustrates the application of the above mentioned optimization loop both at cruise and hover reference flight conditions for such a helicopter. The algorithm pursues the minimization of the total pressure losses at the air intakes while keeping the flow distortion at the engine inlet at the lowest level; regarding the exhausts, the back-pressure is minimized in order to increase the power output of the engine while preserving the entrainment ratio. The results highlight significantly improved performance margins with respect to the baseline both for intakes and exhaust.