Sensitivity and uncertainty analysis of TRACE Physical Model Parameters based on PSBT benchmark using Gaussian process emulator

Chen Wang, Xu Wu, Tomasz Kozlowski

Research output: Contribution to conferencePaper

Abstract

For best estimate thermal-hydraulics codes like TRACE and RELAP5, one major source of uncertainties is the inaccuracy of closure laws (correlations) which are used to describe transfer terms in balance equations. These closure laws were originally studied in separate-effect experiments but are implemented in thermal-hydraulics codes and used for different conditions. Thus, the model parameters involved in such closure laws may have significant influences on model outputs but are subject to considerable uncertainties. The aim of this paper is to perform sensitivity and uncertainty study with respect to selected physical model parameters in TRACE. The PSBT steady-state void fraction data is used as Quantity-of-Interest (QoI). Statistics of these physical model parameters are obtained by inverse Uncertainty Quantification (UQ) from a companion paper. Sensitivity Analysis (SA) aims at determining how uncertain input parameters contribute to the variations of outputs. In this paper, the Sobol' indices are used as a sensitivity measure, which quantify how the variation in a QoI can be apportioned to each input factor. Based on the results from SA, several input parameters that have significant effects on the QoI are selected for the UQ process. The prediction uncertainty is evaluated by considering the propagation of uncertainties in selected TRACE physical model parameters. As thousands of TRACE runs are needed for the sensitivity and uncertainty studies, the use of direct Monte Carlo sampling is not a viable solution. We developed Gaussian Process (GP) emulator as a surrogate model of TRACE to reduce the computation time substantially.

Original languageEnglish (US)
StatePublished - Jan 1 2016
Event17th International Topical Meeting on Nuclear Reactor Thermal Hydraulics, NURETH 2017 - Xi'an, Shaanxi, China
Duration: Sep 3 2017Sep 8 2017

Other

Other17th International Topical Meeting on Nuclear Reactor Thermal Hydraulics, NURETH 2017
CountryChina
CityXi'an, Shaanxi
Period9/3/179/8/17

Fingerprint

Uncertainty analysis
sensitivity analysis
Sensitivity analysis
closure law
hydraulics
sensitivity
output
Hydraulics
Uncertainty
Void fraction
voids
sampling
statistics
propagation
Statistics
estimates
Sampling
predictions

Keywords

  • Gaussian Process
  • Physical Model Uncertainty
  • PSBT
  • Sensitivity and Uncertainty Analysis

ASJC Scopus subject areas

  • Nuclear Energy and Engineering
  • Instrumentation

Cite this

Wang, C., Wu, X., & Kozlowski, T. (2016). Sensitivity and uncertainty analysis of TRACE Physical Model Parameters based on PSBT benchmark using Gaussian process emulator. Paper presented at 17th International Topical Meeting on Nuclear Reactor Thermal Hydraulics, NURETH 2017, Xi'an, Shaanxi, China.

Sensitivity and uncertainty analysis of TRACE Physical Model Parameters based on PSBT benchmark using Gaussian process emulator. / Wang, Chen; Wu, Xu; Kozlowski, Tomasz.

2016. Paper presented at 17th International Topical Meeting on Nuclear Reactor Thermal Hydraulics, NURETH 2017, Xi'an, Shaanxi, China.

Research output: Contribution to conferencePaper

Wang, C, Wu, X & Kozlowski, T 2016, 'Sensitivity and uncertainty analysis of TRACE Physical Model Parameters based on PSBT benchmark using Gaussian process emulator' Paper presented at 17th International Topical Meeting on Nuclear Reactor Thermal Hydraulics, NURETH 2017, Xi'an, Shaanxi, China, 9/3/17 - 9/8/17, .
Wang C, Wu X, Kozlowski T. Sensitivity and uncertainty analysis of TRACE Physical Model Parameters based on PSBT benchmark using Gaussian process emulator. 2016. Paper presented at 17th International Topical Meeting on Nuclear Reactor Thermal Hydraulics, NURETH 2017, Xi'an, Shaanxi, China.
Wang, Chen ; Wu, Xu ; Kozlowski, Tomasz. / Sensitivity and uncertainty analysis of TRACE Physical Model Parameters based on PSBT benchmark using Gaussian process emulator. Paper presented at 17th International Topical Meeting on Nuclear Reactor Thermal Hydraulics, NURETH 2017, Xi'an, Shaanxi, China.
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