Experiences with nonintrusive polynomial Chaos and stochastic collocation methods for uncertainty analysis and design
13 Mar 2009 | Online Presentations | Contributor(s): Michael S. Eldred
Non—intrusive polynomial chaos expansion (PCE) and stochastic collocation (SC) methods are attractive
techniques for uncertainty quantification due to their abilities to produce functional representations of stochastic
variability and to achieve exponential convergence rates in statistics of interest. Whereas PCE estimates coefficients
for known orthogonal polynomial basis functions, SC forms Lagrange interpolants for known coefficients. The latest
results in comparing PCE and SC and embedding these methods within design under uncertainty will be presented.