Probabilistic Aspects of Scramjet Design

Abstract

Scramjet design is characterized by a multitude of design variables influencing a highly nonlinear and complex system. Methods such as mean line calculations, high fidelity computational fluid dynamics, and empirical studies are generally used to derive aircraft engine performance. Because of the high complexity and the incomplete knowledge of hypersonic flow regimes, the question of robust design arises in the given context and leads to the need of probabilistic methodology. In this paper a probabilistic approach to scramjet engine design assessing both inflow and model uncertainty is presented. The two different types of uncertainty are quantified with respect to their different nature by use of a two-step bootstrap methodology. A descriptive sampling Monte Carlo method is employed to propagate the quantified uncertainties through the engine model to exemplify the high sensitivity of net thrust vector to present uncertainties and to analyze the correlation between the parameters variations.

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