Title | Uncertainty Quantification for Complex Multiscale Systems |
Publication Type | Conference Presentation |
Year of Publication | 2016 |
Authors | K. Bhat S, Mebane DS, Mahapatra P, Storlie CB |
Date Published | April 5-8, 2016 |
Abstract | Multiscale modeling efforts must adequately quantify the effect of both parameter uncertainty and model discrepancy across scale. Advancements in uncertainty quantification using Bayesian calibration are described; a dynamic discrepancy approach to upscale uncertainty, functional inputs and extrapolation uncertainty, and a large parameter space. For emulation and discrepancy modeling, a Bayesian Smoothing Spline ANOVA (BSS-ANOVA) approach is utilized. These approaches are applied here to applications in chemical kinetics and carbon capture technology, with wide ranging impact. |