Uncertainty Quantification and Propagation Methods for Hypersonic Airbreathing Launch Vehicle System Analysis

Abstract

Because of the extreme environments experienced by airframe and engine, potential hypersonic airbreathing vehicle technology investment areas are nearly endless. What is needed is a way to prioritize this investment for maximum payoff. To that end, a modular method has been developed for analyzing conceptual hypersonic airbreathing vehicle uncertainty and sensitivity information that provides critical information about performance possibilities. This information also anchors the more rapid uncertainty analysis methods that are compatible with optimization as demonstrated in the NASA Hypersonic NRA Boeing task “System-Level Optimization with Uncertainty.” By leveraging work done on prior programs as well as Boeing’s Hypersonic MDAO demonstration program, this project has developed an efficient and robust uncertainty analysis capability for NASA. The analysis system starts with basic hypersonic analysis modules then adds new, modular uncertainty analyses that are compatible with a wide variety of hypersonic vehicle systems. The system is then exercised using uncertainty source variables that have been both developed and collected from other sources during this research. Variable sensitivities and output distribution characteristics are the result and can be used to gain insights into vehicle design, margins and technology investment in addition to providing anchor points for probabilistic optimization. Variable assumption sensitivity and output distribution results with respect to aerodynamic forces, propulsion forces, atmospheric conditions, aerothermal factors and subsystem weights are presented. A ranking of the variable effects shows a strong influence due to subsystem weights, and a selected group of propulsion factors.