Search

International audience; The French Space Agency (Centre National d'Etudes Spatiales-CNES), the UK Space Agency (UKSA), Reaction Engines Limited (REL) and the French Aerospace Lab (Office National d'Etudes et de Recherches Aérospatiales-ONERA) share a common interest for future space launch architectures and technologies. Preliminary results of a joint study are presented in this paper with the main objective of assessing and quantifying the potential advantages and benefits of air-breathing propulsion technology developed by REL named SABRE (Synergetic Air-Breathing Rocket Engine) for future launch architectures. In that purpose, a conceptual study of two alternative Two-Stage-To-Orbit (TSTO) vehicles is carried out using the SABRE air-breathing rocket engine and a LOx/CH4 rocket engine (for the second stage) for the injection of a 15t payload into low Earth orbit. Different analyses are carried out using a coupled multidisciplinary process involving propulsion, aerodynamics, sizing and trajectory optimizations. Some key influential parameters and intricate behaviors are analyzed through sensitivity to the stage separation conditions. As a result, these analyses provide insight into technological requirements to achieve the target mission using these types of advanced propulsion technologies.

Launch vehicle design is a Multidisciplinary Design Optimization problem whose objective is to find the launch vehicle architecture providing the optimal performance while ensuring the required reliability. In order to obtain an optimal solution, the early design phases are essential for the design process and are characterized by the presence of uncertainty due to the involved physical phenomena and the lack of knowledge on the used models. This thesis is focused on methodologies for multidisciplinary analysis and optimization under uncertainty for launch vehicle design. Three complementary topics are tackled. First, two new formulations have been developed in order to ensure adequate interdisciplinary coupling handling. Then, two new reliability techniques have been proposed in order to take into account the various natures of uncertainty, involving surrogate models and efficient sampling methods.Eventually, a new approach of constraint handling for optimization algorithm “Covariance Matrix Adaptation - Evolutionary Strategy” has been developed to ensure the feasibility of the optimal solution. All the proposed methods have been compared to existing techniques in literature on analysis and design test cases of launch vehicles. The results illustrate that the proposed approaches allow the improvement of the efficiency of the design process and of the reliability of the found solution., La conception de lanceurs est un problème d'optimisation multidisciplinaire dont l'objectif est de trouver l'architecture du lanceur qui garantit une performance optimale tout en assurant un niveau de fiabilité requis. En vue de l'obtention de la solution optimale, les phases d'avant-projet sont cruciales pour le processus de conception et se caractérisent par la présence d'incertitudes dues aux phénomènes physiques impliqués et aux méconnaissances existantes sur les modèles employés. Cette thèse s'intéresse aux méthodes d'analyse et d'optimisation multidisciplinaire en présence d'incertitudes afin d'améliorer le processus de conception de lanceurs. Trois sujets complémentaires sont abordés. Tout d'abord, deux nouvelles formulations du problème de conception ont été proposées afin d'améliorer la prise en compte des interactions disciplinaires. Ensuite, deux nouvelles méthodes d'analyse de fiabilité, permettant de tenir compte d'incertitudes de natures variées, ont été proposées, impliquant des techniques d'échantillonnage préférentiel et des modèles de substitution.Enfin, une nouvelle technique de gestion des contraintes pour l'algorithme d'optimisation « Covariance Matrix Adaptation - Evolutionary Strategy » a été développée, visant à assurer la faisabilité de la solution optimale. Les approches développées ont été comparées aux techniques proposées dans la littérature sur des cas tests d'analyse et de conception de lanceurs. Les résultats montrent que les approches proposées permettent d'améliorer l'efficacité du processus d'optimisation et la fiabilité de la solution obtenue.

This article describes a two stage Reliability-Based Design Optimization (RBDO) algorithm. The first stage consists of solving an approximated RBDO problem using meta-models. In order to use gradient-based techniques, the sensitivity of failure probabilities are derived with respect to hyperparameters of random variables as well as, and this is a novelty, deterministic variables. The second stage focuses on the local refinement of the meta-models around the first stage solution using generalized “max-min” samples. The approach is demonstrated on three examples including a crashworthiness problem with 11 random variables and 10 probabilistic constraints.

In the context of the design of partially reusable launch vehicles, different alternatives may be investigated to recover the first stage while minimizing the costs of reusability and maximizing the performance and reliability. In this paper, a winged configuration of reusable first stage, called glide-back, is studied. This architecture uses the main propulsion system of the first stage to perform a boost-back burn and return to the landing site by a gliding mode using additional lifting surfaces. A focus is made on the design of a reusability kit that can be added to a classical stage to provide it with reusability capabilities. The tradeoff between the design of the reusability kit and its impact on the ascent phase, staging point and global performance of the vehicle is investigated through aerodynamics and trajectory analyses.