Title: Quantification of Uncertainty in High-dimensional Stochastic Problems using Adaptive Sparse Grids Speaker: John D Jakeman, Department of Mathematics, Australian National University Date/Time: Thursday, July 29, 2010 at 10am – 11am Location: CSRI Building/Room 90 (Sandia NM) Brief Abstract: Sparse grids have been frequently used for interpolation and integration of high-dimensional functions. However sparse grids can also be used to efficiently quantify uncertainty in high-dimensional stochastic problems. Sparse grids are extremely useful when only a small number of interactions between function variables contribute significantly to the system response. In such cases, which often occur in practice, high rates of convergence can be obtained even for highly-nonlinear models. In this talk I will present two forms of adaptive sparse grid algorithms that utilize local smoothness and low-effective dimensionality. Analytical and numerical convergence will be demonstrated and a number of numerical examples will be presented.CSRI POC: Michael Eldred, 505- 844-6479 |