Uncertainty quantification guided robust design for nanoparticles' morphology

DOI10.1016/j.cma.2018.03.027zbMath1440.82014OpenAlexW2794691459WikidataQ130056084 ScholiaQ130056084MaRDI QIDQ1985529

M. Razi, L. Dal Negro, Robert M. Kirby, Carlo Forestiere, Yanyan He

Publication date: 7 April 2020

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cma.2018.03.027

zbMATH Keywords

uncertaintysensitivity analysisrobust designfield enhancementgeneralized polynomial chaos expansionmetal nanoparticles

Mathematics Subject Classification ID

Statistical mechanics of nanostructures and nanoparticles (82D80)

Related Items (2)

Mixed aleatory and epistemic uncertainty propagation using Dempster-Shafer theory ⋮ Bayesian neural networks for uncertainty quantification in data-driven materials modeling

Uses Software

• nwSpGr

Cites Work

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• A methodology for performing global uncertainty and sensitivity analysis in systems biology
• The orthogonal development of non-linear functionals in series of Fourier-Hermite functionals
• The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations
• Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates

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