A computationally efficient and cost effective simulation framework has been implemented to perform design space exploration and multi-objective optimization for a conceptual regenerative rotorcraft powerplant configuration at mission level. The proposed framework is developed by coupling a comprehensive rotorcraft mission analysis code with a design space exploration and optimization package. The overall approach is deployed to design and optimize the powerplant of a reference twin-engine light rotorcraft, modeled after the Bo105 helicopter, manufactured by Airbus Helicopters. Initially, a sensitivity analysis of the regenerative engine is carried out to quantify the relationship between the engine thermodynamic cycle design parameters, engine weight, and overall mission fuel economy. Second, through the execution of a multi-objective optimization strategy, a Pareto front surface is constructed, quantifying the optimum trade-off between the fuel economy offered by a regenerative engine and its associated weight penalty. The optimum sets of cycle design parameters obtained from the structured Pareto front suggest that the employed heat effectiveness is the key design parameter affecting the engine weight and fuel efficiency. Furthermore, through quantification of the benefits suggested by the acquired Pareto front, it is shown that the fuel economy offered by the simple cycle rotorcraft engine can be substantially improved with the implementation of regeneration technology, without degrading the payload-range capability and airworthiness (one-engine-inoperative) of the rotorcraft.
A system-level methodology for fast multi-objective design space exploration
