Abstract
Traditional techniques like Monte-Carlo (MC) methods have been widely used to quantify the effect of uncertainties in numerical models. However, MC solution statistics converge slowly requiring many simulations. In this paper, the Polynomial Chaos Expansion (PCE) and Control Variate (CV) method, which display faster rates of convergence are investigated. A non-intrusive formulation of a third order PCE and the CV method are applied to quantify uncertainties in a ray-tracing model, which are shown to have good agreement with MC results and experimental measurements.
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