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research-article

Heat Transfer Modeling of Spent Nuclear Fuel Using Uncertainty Quantication and Polynomial Chaos Expansion.

[+] Author and Article Information
Imane Khalil

Assistant Professor, Mechanical Engineering
ikhalil@sandiego.edu

Quinn Pratt

Undergraduate Research Assistant
quinnpratt@sandiego.edu

Harrison Samuel Schmachtenberger

Undergraduate Research Assistant, Shiley-Marcos School of Engineering, 5998 Alaclá Park, University of San Diego, San Diego, CA 92110
harrisons@sandiego.edu

Roger G. Ghanem

Professor, Civil Engineering, Sonny Astani Department of Civil and Environmental Engineering, 3610 S. Vermont St., University of Southern California, Los Angeles, CA 90089
ghanem@usc.edu

1Corresponding author.

ASME doi:10.1115/1.4037501 History: Received March 27, 2017; Revised June 07, 2017

Abstract

A novel method that incorporates Uncertainty Quantification (UQ) into numerical simulations of heat transfer for a 9×9 square array of Spent Nuclear Fuel (SNF) assemblies in a BoilingWater Reactor (BWR) is presented in this paper. Using a range of fuel burn up power, the results predict the maximum mean temperature at the center of the 9×9 BWR fuel assembly to be 462K. Current related modeling techniques used to predict the heat transfer and the maximum temperature inside SNF assemblies rely on commercial codes and address the uncertainty in the input parameters by running separate simulations for different input parameters models. The utility of leveraging Polynomial Chaos Expansion (PCE) to develop a surrogate model that permits the efficient evaluation of the distribution of temperature and heat transfer while accounting for all uncertain input parameters to the model is explored and validated for a complex case of heat transfer that could be substituted with other problems of intricacy. UQ computational methods generated results that are encompassing of continuous ranges of variable parameters that also served to conduct sensitivity analysis on heat transfer simulations of spent nuclear fuel assemblies with respect to physically relevant parameters.

Copyright (c) 2017 by ASME
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