Helen Cleaves

College of Sciences

Works (2)

Updated: July 5th, 2023 14:41

2021 article

Structure exploiting methods for fast uncertainty quantification in multiphase flow through heterogeneous media

Cleaves, H., Alexanderian, A., & Saad, B. (2021, September 8). COMPUTATIONAL GEOSCIENCES.

By: H. Cleaves n, A. Alexanderian n & B. Saad*

author keywords: Uncertainty quantification; Surrogate models; Dimension reduction; Multiphase flow; Sensitivity analysis; Spectral representations
TL;DR: A computational framework for dimension reduction and surrogate modeling to accelerate uncertainty quantification in computationally intensive models with high-dimensional inputs and function-valued outputs and demonstrates the effectiveness of the proposed surrogate modeling approach with a comprehensive set of numerical experiments. (via Semantic Scholar)
Source: Web Of Science
Added: September 20, 2021

2019 journal article

DERIVATIVE-BASED GLOBAL SENSITIVITY ANALYSIS FOR MODELS WITH HIGH-DIMENSIONAL INPUTS AND FUNCTIONAL OUTPUTS

SIAM JOURNAL ON SCIENTIFIC COMPUTING, 41(6), A3524–A3551.

By: H. Cleaves*, A. Alexanderian*, H. Guy, R. Smith* & M. Yu

author keywords: global sensitivity analysis; DGSMs; functional Sobol' indices; Karhunen-Loeve expansions
TL;DR: A framework for derivative-based global sensitivity analysis (GSA) for models with high-dimensional input parameters and functional outputs is presented and the strategy for a nonlinear ODE model of cholera epidemics and for elliptic PDEs is illustrated. (via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being (OpenAlex)
Sources: Web Of Science, NC State University Libraries
Added: August 3, 2020

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