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University of Illinois at Urbana-Champaign

Inverse uncertainty quantification of trace physical model parameters using Bayesian analysis

Abstract

dc:description

Forward quantification of uncertainties in code responses require knowledge of input model parameter uncertainties. Nuclear thermal-hydraulics codes such as RELAP5 and TRACE do not provide any information on physical model parameter uncertainties. A framework was developed to quantify input model parameter uncertainties based on Maximum Likelihood Estimation (MLE), Bayesian Maximum A Priori (MAP), and Markov Chain Monte Carlo (MCMC) algorithm for physical models using relevant experimental data. The objective of the present work is to perform the sensitivity analysis of the code input (physical model) parameters in TRACE and calculate their uncertainties using an MLE, MAP and MCMC algorithm, with a particular focus on the subcooled boiling model. The OECD/NEA BWR full-size fine-mesh bundle test (BFBT) data will be used to quantify selected physical model uncertainty of the TRACE code. The BFBT is based on a multi-rod assembly with measured data available for single or two-phase pressure drop, axial and radial void fraction distributions, and critical power for a wide range of system conditions. In this thesis, the steady-state cross-sectional averaged void fraction distribution from BFBT experiments is used as the input for inverse uncertainty algorithm, and the selected physical model’s Probability Distribution Function (PDF) is the desired output quantity.

Degree

thesis:*
Name thesis:degree_name
M.S.
Level thesis:degree_level
Thesis
Discipline thesis:degree_discipline
Nuclear, Plasma, & Radiological Engineering
Grantor
University of Illinois at Urbana-Champaign
Year dc:date
2016

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Hu, Guojun
Contributors dc:contributor
  • Kozlowski, Tomasz

Subjects

dc:subject × 5

Rights

dc:rights
Statement dc:rights
  • Copyright 2015 Guojun Hu
Language dc:language
en

Identifiers

dc:identifier.*
Handle dc:identifier
http://hdl.handle.net/2142/89042
OAI identifier oai:identifier
oai:www.ideals.illinois.edu:2142/89042

Chain of custody

source
Harvested from
University of Illinois - Urbana-Champaign
Base URL
www.ideals.illinois.edu/oai-pmh
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Hu, Guojun. Inverse uncertainty quantification of trace physical model parameters using Bayesian analysis. Thesis thesis, University of Illinois at Urbana-Champaign, 2016. http://hdl.handle.net/2142/89042