Ranking Based Model-Form Uncertainty Quantification for a Multi-fidelity Design Approach

Abstract

Computer simulation based design processes are being extensively used in preliminary design phase of complex aerospace vehicles like scramjet powered hypersonic vehicles. Analysis tools of varying fidelity are generally used to assess the system performance metrics. Often there is a constraint on the number of simulations using high fidelity analysis tools to predict the performance metrics, due to attendant computational demands. A low fidelity analysis tool complemented with an uncertainty model enables the designer to make better design decisions in such situations. A novel approach based on ranks is proposed in this study to aggregate high fidelity information in a cost effective manner. Based on this information, a cumulative distribution function for the difference between high fidelity and low fidelity responses is constructed. The approach is demonstrated initially for a synthetic example and subsequently for quantification of uncertainty in a typical disciplinary metric for hypersonic vehicle design.