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

Global and Local Multidisciplinary Design Optimization of Expendable Launch Vehicles

Defining Support Requirements During Conceptual Design of Reusable Launch Vehicles

Current methods for defining the operational support requirements of new systems are data intensive and require significant design information. Methods are being developed to aid in the analysis process of defining support requirements for new launch vehicles during their conceptual design phase that work with the level of information available during this phase. These methods will provide supp...

Estimating Logistics Support of Reusable Launch Vehicles during Conceptual Design

Methods exist to define the logistics support requirements for new aircraft concepts but are not directly applicable to new launch vehicle concepts. In order to define the support requirements and to discriminate among new technologies and processing choices for these systems, NASA Langley Research Center (LaRC) is developing new analysis methods. This paper describes several methods under deve...

Generic Simulation Models of Reusable Launch Vehicles

Analyzing systems by means of simulation is necessarily a time consuming process. This becomes even more pronounced when models of multiple systems must be compared. In general, and even more so in today’s fast-paced environment, competitive pressure does not allow for waiting on the results of a lengthy analysis. That competitive pressure also makes it more imperative that the processing perfo...

Multidisciplinary Design Optimization of Solid Launch Vehicle Using Hybrid Algorithm

A new approach is proposed incorporating heuristic optimization algorithm with a switch to a local search algorithm for the multidisciplinary design of solid launch vehicle at conceptual level. Heuristic optimization algorithms such as Genetic Algorithm often may locate near optimum solutions at the expense of large function evaluations. Local search algorithms including both gradient and non g...