Gaussian Process–Based Inverse Uncertainty Quantification for TRACE Physical Model Parameters Using Steady-State PSBT Benchmark-Reference-Cited by-同舟云学术

Gaussian Process–Based Inverse Uncertainty Quantification for TRACE Physical Model Parameters Using Steady-State PSBT Benchmark

Published:2018-08-10 Issue:1-2 Volume:193 Page:100-114
ISSN:0029-5639
Container-title:Nuclear Science and Engineering
language:en
Short-container-title:Nuclear Science and Engineering

Author:

Wang Chen¹^ORCID,Wu Xu²,Kozlowski Tomasz¹

Affiliation:

1. University of Illinois at Urbana-Champaign, Department of Nuclear, Plasma and Radiological Engineering, 223 Talbot Laboratory, 104 South Wright Street, Urbana, Illinois 61801

2. Massachusetts Institute of Technology, Department of Nuclear Science and Engineering, Cambridge, Massachusetts

Funder

U.S. Department of Energy, Office of Nuclear Energy

Publisher

Informa UK Limited

Subject

Nuclear Energy and Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/00295639.2018.1499279

Reference33 articles.

1. Historical insights in the development of Best Estimate Plus Uncertainty safety analysis

2. Uncertainty and sensitivity analysis of a post-experiment calculation in thermal hydraulics

3. Inverse uncertainty quantification of reactor simulations under the Bayesian framework using surrogate models constructed by polynomial chaos expansion

4. Bayesian calibration of computer models

5. Inverse uncertainty quantification using the modular Bayesian approach based on Gaussian process, Part 1: Theory

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