Non-intrusive Uncertainty Quantification by Combination of Reduced Basis Method and Regression-based Polynomial Chaos Expansion

2018 ◽  
pp. 169-184
Author(s):  
Mehrdad Raisee ◽  
Dinesh Kumar ◽  
Chris Lacor
Keyword(s):  
Uncertainty Quantification ◽  
Polynomial Chaos ◽  
Polynomial Chaos Expansion ◽  
Reduced Basis Method ◽  
Chaos Expansion ◽  
Reduced Basis ◽  
Basis Method

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

2017 ◽  
Vol 140 (2) ◽  
Author(s):  
Imane Khalil ◽  
Quinn Pratt ◽  
Harrison Schmachtenberger ◽  
Roger Ghanem
Keyword(s):  
Heat Transfer ◽  
Fuel Assembly ◽  
Uncertainty Quantification ◽  
Nuclear Fuel ◽  
Polynomial Chaos ◽  
Spent Nuclear Fuel ◽  
Polynomial Chaos Expansion ◽  
Complex Case ◽  
Chaos Expansion ◽  
Input Parameters

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 boiling water reactor (BWR) is presented in this paper. The results predict the maximum mean temperature at the center of the 9 × 9 BWR fuel assembly to be 462 K using a range of fuel burn-up power. 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. 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 continuous ranges of variable parameters that also served to conduct sensitivity analysis on heat transfer simulations of SNF assemblies with respect to physically relevant parameters. A two-dimensional (2D) model is used to describe the physical processes within the fuel assembly, and a second-order PCE is used to characterize the dependence of center temperature on ten input parameters.

Uncertainty quantification and sensitivity analysis of thermoacoustic stability with non-intrusive polynomial chaos expansion

2018 ◽  
Vol 189 ◽  
pp. 300-310 ◽  
Author(s):  
Alexander Avdonin ◽  
Stefan Jaensch ◽  
Camilo F. Silva ◽  
Matic Češnovar ◽  
Wolfgang Polifke
Keyword(s):  
Sensitivity Analysis ◽  
Uncertainty Quantification ◽  
Polynomial Chaos ◽  
Polynomial Chaos Expansion ◽  
Chaos Expansion
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