Multiobjective and Multipoint Optimization of a Heavy Class Helicopter Engine Installation Using Evolutionary Algorithms

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 in reaching 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 the home made genetic algorithm GeDEA, and applied it to engine installation design of a heavy-class helicopter, as well as to aircraft components optimization problems. This paper illustrates the application of the GeDEA-based optimization loop both at forward and hover reference flight conditions for such helicopter. The algorithm pursues the minimization of the total pressure losses at the inlets while keeping the flow distortion at the engine inlet at the lowest level; regarding the exhaust, the back-pressure is minimized in order to increase the power output of the engine while preserving the entrainment ratio. The results highlight significant improved performance margins in all the components.