Bayesian uncertainty quantification of tristructural isotropic particle fuel silver release: Decomposing model inadequacy plus experimental noise and parametric uncertainties-Reference-Cited by-同舟云学术

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Bayesian uncertainty quantification of tristructural isotropic particle fuel silver release: Decomposing model inadequacy plus experimental noise and parametric uncertainties

Published:2024-01 Issue: Volume:588 Page:154790
ISSN:0022-3115
Container-title:Journal of Nuclear Materials
language:en
Short-container-title:Journal of Nuclear Materials

Author:

Dhulipala Somayajulu L.N.^ORCID,Toptan Aysenur^ORCID,Che Yifeng^ORCID,Schwen Daniel^ORCID,Sweet Ryan T.^ORCID,Hales Jason D.^ORCID,Novascone Stephen R.^ORCID

Publisher

Elsevier BV

Subject

Nuclear Energy and Engineering,General Materials Science,Nuclear and High Energy Physics

Reference41 articles.

1. Globally centered autocovariances in MCMC;Agarwal;J. Comput. Graph. Stat.,2022

2. Quantification of model uncertainty: calibration, model discrepancy, and identifiability;Arendt;ASME J. Mech. Des.,2012

3. Sapium: a generic framework for a practical and transparent quantification of thermal-hydraulic code model input uncertainty;Baccou;Nucl. Sci. Eng.,2020

4. A Markov chain Monte Carlo version of the genetic algorithm differential evolution: easy Bayesian computing for real parameter spaces;Braak;Stat. Comput.,2006

5. Application of kriging and variational bayesian monte carlo method for improved prediction of doped UO2 fission gas release;Che;Ann. Nucl. Energy,2021

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