Advanced Space Vehicle Design Taking into Account Multidisciplinary Couplings and Mixed Epistemic/Aleatory Uncertainties

Space vehicle design is a complex process involving numerous disciplines such as aerodynamics, structure, propulsion and trajectory. These disciplines are tightly coupled and may involve antagonistic objectives that require the use of specific methodologies in order to assess trade-offs between the disciplines and to obtain the global optimal configuration. Generally, there are two ways to handle the system design. On the one hand, the design may be considered from a disciplinary point of view (a.k.a. Disciplinary Design Optimization): the designer of each discipline has to design its subsystem (e.g. engine) taking the interactions between its discipline and the others (interdisciplinary couplings) into account. On the other hand, the design may also be considered as a whole: the design team addresses the global architecture of the space vehicle, taking all the disciplinary design variables and constraints into account at the same time. This methodology is known as Multidisciplinary Design Optimization (MDO) and requires specific mathematical tools to handle the interdisciplinary coupling consistency. In the first part of this chapter, we present the main classical techniques to efficiently tackle the interdisciplinary coupling satisfaction problem. In particular, an MDO decomposition strategy based on the “Stage-Wise decomposition for Optimal Rocket Design” formulation is described. This method allows the design process to be decentralized according to the different subsystems (e.g. launch vehicle stages) and reduces the computational cost compared to classical MDO methods. Furthermore, when designing an innovative space vehicle including breakthrough technologies (e.g. launch vehicle with new kind of propulsion, new aerodynamics configuration), one has to cope with numerous uncertainties relative to the involved technology models (epistemic uncertainties) and the effects of these on the global design and on the interdisciplinary coupling satisfaction. Moreover, aleatory uncertainties inherent to the physical phenomena occurring during the space vehicle mission (e.g. solar fluxes, wind gusts) must also be considered in order to accurately estimate the performance and reliability of the vehicle. The combination of both epistemic and aleatory uncertainties requires dedicated techniques to manage the computational cost induced by uncertainty handling. The second part of this chapter is devoted to the handling of design process in the presence of uncertainties. Firstly, we describe a design methodology that enables to define the design rules (e.g. safety factors) taking both aleatory and epistemic uncertainties into account. Secondly, we present new MDO methods that allow to decompose the design process while maintaining the interdisciplinary functional coupling relationships between the disciplines in the presence of uncertainties.