AERODYNAMIC SHAPE OPTIMIZATION OF AIR-INTAKES OF A HELICOPTER TURBOSHAFT

The research project HEAVYcOPTer, a sub task of the European R&D program Clean-Sky GRC2 [1], is devoted to the efficient design and the shape optimization of the AgustaWestland AW101 helicopter turboshaft engine intake and exhaust system, to be carried out by means of advanced multi-objective optimization algorithms coupled with CFD Navier-Stokes solvers. The present paper describes the outcomes of HEAVYcOPTer in relation to the air intakes shape optimisation activities. This paper describes the technical details of such program. The optimisation method chosen for the redesign of the engine installation involves the application of the state of the art genetic algorithm GDEA, developed at the University of Padova and successfully applied in several fluid-dynamics applications, especially in the field of turbo-machinery. For the present application, the set of geometrical designs constituting the genetic algorithm population are generated by means of morphing the original CFD model surface mesh: shapes are applied to baseline surface nodes with a displacement intensity driven by the GA chosen scaling factors. Then, CFD models of new designs are automatically generated and analyzed by the flow solver, returning to the GA the evaluation of the selected objective functions required in order to evolve the population in the next step of the evolutionary process. AW101 intakes have been optimised following a multi-objective/multi-point approach, minimizing inlet total pressure loss in both hovering and forward flight conditions simultaneously; optimised solutions were also constrained so as to not exceed the total pressure distortion level at the engine aerodynamic interface plane, so as to ensure inlet/engine compatibility with respect to the compressor surge limit. This approach ensured the improvement of the engine/airframe integration efficiency for the overall rotorcraft flight envelop, reducing fuel burn and increasing the helicopter propulsive efficiency.