182 citations · 442 across the 13 of their papers we have counts for
Showing 2018Show all
3 papers · 1 filter
stat.AP2018★ 45 cited
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…
stat.AP2018★ 68 cited
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…
stat.CO2018★ 136 cited
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…