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

Abstract

International audienceSpace 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. 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

Multidisciplinary Design Optimization of Reusable Launch Vehicles for Different Propellants and Objectives

“…In order to meet the new design challenges of future launch vehicles, various multidisciplinary design studies have recently been conducted. Balesdent et al [21] studied, among other things, the influence of technological uncertainties (e.g., new propellant combinations or reusable rocket engines) on the design process of future launch vehicles. Briese et al [22] presented a modular multidisciplinary modeling framework for reusable launch vehicles with a particular focus on the trajectory optimization of the ascent and descent phases.…”

Multidisciplinary Design Optimization of Reusable Launch Vehicles for Different Propellants and Objectives

“…To meet the new design challenges of future launch vehicles, various multidisciplinary design studies have recently been conducted. Balesdent et al [21] studied, among other things, the influence of technological uncertainties (e.g., new propellant combinations or reusable rocket engines) on the design process of future launch vehicles. Briese et al [22] presented a modular multidisciplinary modeling framework for reusable launch vehicles with a particular focus on the trajectory optimization of the ascent and descent phases.…”

Multi-Objective Multidisciplinary Design Optimization Approach for Partially Reusable Launch Vehicle Design

“…This MDA involves computationally expensive coupled models (aerodynamics, propulsion, structural design, trajectory, etc.) [2].…”