136 citations · 314 across the 7 of their papers we have counts for
7 papers
Inverse Uncertainty Quantification by Hierarchical Bayesian Modeling and Application in Nuclear System Thermal-Hydraulics Codes
Chen Wang, Xu Wu, Tomasz Kozlowski
Inverse Uncertainty Quantification (IUQ) method has been widely used to quantify the uncertainty of Physical Model Parameters (PMPs) in nuclear Thermal Hydraulics (TH) systems. Thi…
A Comprehensive Survey of Inverse Uncertainty Quantification of Physical Model Parameters in Nuclear System Thermal-Hydraulics Codes
Xu Wu, Ziyu Xie, Farah Alsafadi +1
Uncertainty Quantification (UQ) is an essential step in computational model validation because assessment of the model accuracy requires a concrete, quantifiable measure of uncerta…
Assessment of continuous and discrete adjoint method for sensitivity analysis in two-phase flow simulations
Guojun Hu, Tomasz Kozlowski
The efficient method for computing the sensitivities is the adjoint method. The cost of solving an adjoint equation is comparable to the cost of solving the governing equation. Onc…
Application of discrete adjoint method to sensitivity and uncertainty analysis in steady-state two-phase flow simulations
Guojun Hu, Tomasz Kozlowski
Verification, validation and uncertainty quantification (VVUQ) have become a common practice in thermal-hydraulics analysis. An important step in the uncertainty analysis is the se…
Demonstration of the Relationship between Sensitivity and Identifiability for Inverse Uncertainty Quantification
Xu Wu, Koroush Shirvan, Tomasz Kozlowski
Inverse Uncertainty Quantification (UQ), or Bayesian calibration, is the process to quantify the uncertainties of random input parameters based on experimental data. The introducti…
Inverse Uncertainty Quantification using the Modular Bayesian Approach based on Gaussian Process, Part 2: Application to TRACE
Xu Wu, Tomasz Kozlowski, Hadi Meidani +1
Inverse Uncertainty Quantification (UQ) is a process to quantify the uncertainties in random input parameters while achieving consistency between code simulations and physical obse…
Inverse Uncertainty Quantification using the Modular Bayesian Approach based on Gaussian Process, Part 1: Theory
Xu Wu, Tomasz Kozlowski, Hadi Meidani +1
In nuclear reactor system design and safety analysis, the Best Estimate plus Uncertainty (BEPU) methodology requires that computer model output uncertainties must be quantified in…