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The embodiment design of aeronautic systems proves to be a difficult design phase due to the variability in the system environment; the design is often constrained by atmospheric conditions. These atmospheric conditions appear to be highly variable according to the flight phases of the aircraft. The difficulty when designing air-conditioning systems for civil aircrafts is also inherent to the complexity of the coupling of the nonlinear physical phenomena inside of these systems (multi-physics, multi-scaling). Therefore, the design space appears to be very broad and quite difficult to explore. Embodiment design choices are relating to continuous and discrete design variables while the system effectiveness is extremely sensitive to most of these design variables. There is a lack of tools to support the investigation of the design exploration space and designer decisions at early stages of the design process. In this paper, a method is proposed to generate feasible embodiments and manage the compromise between various design requirements. A digital tool based on the meta-heuristic of Genetic Algorithms (Gas) has been developed to investigate the design problem. The selection of non-dominated solutions (Pareto) is used to identify relevant values for design variables and to facilitate choices among the design solutions of the air conditioning system.

Design space exploration in embodiment design: an application to the design of aircraft air conditioners