Publications

Approaches for quantifying uncertainties in computational modeling for aerospace applications

Schaefer, John; Leyde, Brian; Denham, Casey; Romero, Vicente J.; Schafer, Steven

In the past few decades, advancements in computing hardware and physical modeling capability have allowed computer models such as computational fluid dynamics to accelerate the development cycle of aerospace products. In general, model behavior is well-understood in the heart of the flight envelope, such as the cruise condition for a conventional commercial aircraft. Models have been well validated at these conditions, so the practice of running a single, deterministic solution to assess aircraft performance is sufficient for engineering purposes. However, the aerospace industry is beginning to apply models to configurations at the edge of the flight envelope. In this regime, uncertainty in the model due to its mathematical form, numerical behavior, or model parameters may become important. Uncertainty Quantification is the process of characterizing all major sources of uncertainty in the model and quantifying their effect on analysis outcomes. The goal of this paper is to survey modern uncertainty quantification methodologies and relate them to aerospace applications. Ultimately, uncertainty quantification enables modelers and simulation practitioners to make more informed statements about the uncertainty and associated degree of credibility of model-based predictions.