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Uncertainty Quantification for Incident Helium Flux in Plasma-Exposed Tungsten

In this work, the surface response of a tungsten plasma-facing component was simulated by a cluster-dynamics code, Xolotl, with a focus on quantifying the impact of uncertainty in one of the input parameters to Xolotl, namely, the incident helium …

Compressed Sparse Tensor based Quadrature for Vibrational Quantum Mechanics Integrals

A new method for fast evaluation of high dimensional integrals arising in quantum mechanics is proposed. The method is based on sparse approximation of a high dimensional function followed by a low-rank compression. In the first step, we interpret …

Compressive Sensing with Cross-Validation and Stop-Sampling for Sparse Polynomial Chaos Expansions

Compressive sensing is a powerful technique for recovering sparse solutions of underdetermined linear systems, which is often encountered in uncertainty quantification analysis of expensive and high-dimensional physical models. We perform numerical …

Global Sensitivity Analysis and Estimation of Model Error, toward Uncertainty Quantification in Scramjet Computations

The development of scramjet engines is an important research area for advancing hypersonic and orbital flights. Progress toward optimal engine designs requires accurate flow simulations together with uncertainty quantification. However, performing …

Probabilistic Parameter Estimation in a 2-Step Chemical Kinetics Model for n-Dodecane Jet Autoignition

This paper demonstrates the development of a simple chemical kinetics model designed for autoignition of n-dodecane in air using Bayesian inference with a model-error representation. The model error, i.e. intrinsic discrepancy from a high-fidelity …

Exploring the Interplay of Resilience and Energy Consumption for a Task-based Partial Differential Equations Preconditioner

We discuss algorithm-based resilience to silent data corruptions (SDCs) in a task-based domain-decomposition preconditioner for partial differential equations (PDEs). The algorithm exploits a reformulation of the PDE as a sampling problem, followed …

Partial Differential Equations Preconditioner Resilient to Soft and Hard Faults

We present a domain-decomposition-based preconditioner for the solution of partial differential equations (PDEs) that is resilient to both soft and hard faults. The algorithm reformulates the PDE as a sampling problem, followed by a solution update …

The Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model

We conduct a global sensitivity analysis (GSA) of the Energy Exascale Earth System Model (E3SM), land model (ELM) to calculate the sensitivity of five key carbon cycle outputs to 68 model parameters. This GSA is conducted by first constructing a …

Temporal and Spatial Variation in Peatland Carbon Cycling and Implications for Interpreting Responses of an Ecosystem-Scale Warming Experiment

We are conducting a large-scale, long-term climate change response experiment in an ombrotrophic peat bog in Minnesota to evaluate the effects of warming and elevated CO2 on ecosystem processes using empirical and modeling approaches. To better frame …

Low-Rank Canonical-Tensor Decomposition of Potential Energy Surfaces: Application to Grid-based Diagrammatic Vibrational Green's Function Theory

A new method is proposed for a fast evaluation of high-dimensional integrals of potential energy surfaces (PES) that arise in many areas of quantum dynamics. It decomposes a PES into a canonical low-rank tensor format, reducing its integral into a …