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Uncertainty Quantification Methods for Model Calibration, Validation, and Risk Analysis

In this paper we propose a series of methodologies to address the problems in the NASA Langley Multidisciplinary UQ Challenge. A Bayesian approach is employed to characterize and calibrate the epistemic parameters in problem A, while variance-based …

Validation and Uncertainty Assessment of Extreme-Scale HPC Simulation through Bayesian Inference

Simulation of high-performance computing (HPC) systems plays a critical role in their development - especially as HPC moves toward the co-design model used for embedded systems, tying hardware and software into a unified design cycle. Exploring …

Uncertainty Quantification in the Presence of Limited Climate Model Data with Discontinuities

Uncertainty quantification in climate models is challenged by the sparsity of the available climate data due to the high computational cost of the model runs. Another feature that prevents classical uncertainty analyses from being easily applicable …