Neutronics and fuel performance evaluation of accident tolerant FeCrAl cladding under normal operation conditions X Wu, T Kozlowski, JD Hales Annals of Nuclear Energy 85, 763-775, 2015 | 127 | 2015 |
Inverse Uncertainty Quantification using the Modular Bayesian Approach based on Gaussian Process, Part 1: Theory X Wu, T Kozlowski, H Meidani, K Shirvan Nuclear Engineering and Design 335, 339–355, 2018 | 114 | 2018 |
Kriging-based inverse uncertainty quantification of nuclear fuel performance code BISON fission gas release model using time series measurement data X Wu, T Kozlowski, H Meidani Reliability Engineering & System Safety 169, 422-436, 2017 | 74 | 2017 |
Inverse uncertainty quantification using the modular Bayesian approach based on Gaussian Process, Part 2: Application to TRACE X Wu, T Kozlowski, H Meidani, K Shirvan Nuclear Engineering and Design 335, 417-431, 2018 | 60 | 2018 |
Inverse uncertainty quantification of reactor simulations under the Bayesian framework using surrogate models constructed by polynomial chaos expansion X Wu, T Kozlowski Nuclear Engineering and Design 313, 29-52, 2017 | 40 | 2017 |
Inverse uncertainty quantification of TRACE physical model parameters using sparse gird stochastic collocation surrogate model X Wu, T Mui, G Hu, H Meidani, T Kozlowski Nuclear Engineering and Design 319, 185-200, 2017 | 38 | 2017 |
A Comprehensive Survey of Inverse Uncertainty Quantification of Physical Model Parameters in Nuclear System Thermal-Hydraulics Codes X Wu, Z Xie, F Alsafadi, T Kozlowski Nuclear Engineering and Design 384, 111460, 2021 | 36 | 2021 |
Demonstration of the relationship between sensitivity and identifiability for inverse uncertainty quantification X Wu, K Shirvan, T Kozlowski Journal of computational physics 396, 12-30, 2019 | 33 | 2019 |
Coupling of system thermal–hydraulics and Monte-Carlo code: Convergence criteria and quantification of correlation between statistical uncertainty and coupled error X Wu, T Kozlowski Annals of Nuclear Energy 75, 377-387, 2015 | 30 | 2015 |
Gaussian process–based inverse uncertainty quantification for trace physical model parameters using steady-state psbt benchmark C Wang, X Wu, T Kozlowski Nuclear Science and Engineering 193 (1-2), 100-114, 2019 | 25 | 2019 |
System code evaluation of near-term accident tolerant claddings during boiling water reactor short-term and long-term station blackout accidents X Wu, K Shirvan Nuclear Engineering and Design 356, 110362, 2020 | 22 | 2020 |
Application of Kriging and Variational Bayesian Monte Carlo method for improved prediction of doped UO2 fission gas release Y Che, X Wu, G Pastore, W Li, K Shirvan Annals of Nuclear Energy 153, 108046, 2021 | 20 | 2021 |
Kriging-based surrogate models for uncertainty quantification and sensitivity analysis X Wu, C Wang, T Kozlowski | 20 | 2017 |
Neutronics and fuel performance evaluation of accident tolerant fuel under normal operation conditions X Wu, P Sabharwall, J Hales Idaho National Lab.(INL), Idaho Falls, ID (United States), 2014 | 19 | 2014 |
Surrogate-based inverse uncertainty quantification of TRACE physical model parameters using steady-state PSBT void fraction data C Wang, X Wu, T Kozlowski Proc. 17th Int. Topl. Mtg. Nuclear Reactor Thermal Hydraulics (NURETH-17), 3-8, 2017 | 15 | 2017 |
Metamodel-based inverse uncertainty quantification of nuclear reactor simulators under the Bayesian framework X Wu University of Illinois at Urbana-Champaign, 2017 | 14 | 2017 |
Bayesian inverse uncertainty quantification of a MOOSE-based melt pool model for additive manufacturing using experimental data Z Xie, W Jiang, C Wang, X Wu Annals of Nuclear Energy 165, 108782, 2022 | 12 | 2022 |
Towards improving the predictive capability of computer simulations by integrating inverse Uncertainty Quantification and quantitative validation with Bayesian hypothesis testing Z Xie, F Alsafadi, X Wu Nuclear Engineering and Design 383, 111423, 2021 | 12 | 2021 |
System code evaluation of near-term accident tolerant claddings during pressurized water reactor station blackout accidents Y Jin, X Wu, K Shirvan Nuclear Engineering and Design 368, 110814, 2020 | 12 | 2020 |
Inverse uncertainty quantification by hierarchical bayesian inference for trace physical model parameters based on bfbt benchmark C Wang, X Wu, T Kozlowski Proceedings of NURETH-2019, Portland, Oregon, USA, 2019 | 10 | 2019 |