Xu Wu

Inverse Uncertainty Quantification by Hierarchical Bayesian Modeling and Application in Nuclear System Thermal-Hydraulics Codes

(ArXiv Preprint No. 2305.16622).

Prediction and uncertainty quantification of SAFARI-1 axial neutron flux profiles with neural networks

ANNALS OF NUCLEAR ENERGY, 188.

Bayesian inverse uncertainty quantification of a MOOSE-based melt pool model for additive manufacturing using experimental data

ANNALS OF NUCLEAR ENERGY, 165.

Quantification of Deep Neural Network Prediction Uncertainties for VVUQ of Machine Learning Models

Yaseen, M., & Wu, X. (2022, November 4). NUCLEAR SCIENCE AND ENGINEERING, Vol. 11.

A comprehensive survey of inverse uncertainty quantification of physical model parameters in nuclear system thermal-hydraulics codes

NUCLEAR ENGINEERING AND DESIGN, 384.

Application of Kriging and Variational Bayesian Monte Carlo method for improved prediction of doped UO2 fission gas release

ANNALS OF NUCLEAR ENERGY, 153.

Enhancing the One-Dimensional SFR Thermal Stratification Model via Advanced Inverse Uncertainty Quantification Methods

Nuclear Technology, 10, 1–19.

Structural Health Monitoring of Microreactor Safety Systems Using Convolutional Neural Networks

Towards improving the predictive capability of computer simulations by integrating inverse Uncertainty Quantification and quantitative validation with Bayesian hypothesis testing

NUCLEAR ENGINEERING AND DESIGN, 383.

System code evaluation of near-term accident tolerant claddings during pressurized water reactor station blackout accidents

NUCLEAR ENGINEERING AND DESIGN, 368.

Demonstration of the relationship between sensitivity and identifiability for inverse uncertainty quantification

Journal of Computational Physics, 396, 12–30.

Gaussian Process–Based Inverse Uncertainty Quantification for TRACE Physical Model Parameters Using Steady-State PSBT Benchmark

Nuclear Science and Engineering, 193(1-2), 100–114.

Bayesian calibration and uncertainty quantification for trace based on PSBT benchmark

Transactions of the American Nuclear Society, 118, 419–422. http://www.scopus.com/inward/record.url?eid=2-s2.0-85062963843&partnerID=MN8TOARS

Inverse uncertainty quantification using the modular Bayesian approach based on Gaussian Process, Part 2: Application to TRACE

Nuclear Engineering and Design, 335, 417–431.

Inverse uncertainty quantification using the modular Bayesian approach based on Gaussian process, Part 1: Theory

Nuclear Engineering and Design, 335, 339–355.

Kriging-based inverse uncertainty quantification of nuclear fuel performance code BISON fission gas release model using time series measurement data

Reliability Engineering and System Safety, 169, 422–436.

On the connection between sensitivity and identifiability for inverse uncertainty quantification

Transactions of the American Nuclear Society, 118, 411–414. http://www.scopus.com/inward/record.url?eid=2-s2.0-85062995468&partnerID=MN8TOARS

Sensitivity and uncertainty analysis for fuel performance evaluation of Cr 2 O 3 -doped UO 2 fuel under LB-LOCA

Transactions of the American Nuclear Society, 119, 440–443. http://www.scopus.com/inward/record.url?eid=2-s2.0-85060860913&partnerID=MN8TOARS

System code evaluation of accident tolerant claddings during BWR station blackout accident

Transactions of the American Nuclear Society, 119, 444–447. http://www.scopus.com/inward/record.url?eid=2-s2.0-85060862292&partnerID=MN8TOARS

Validating trace void fraction predictive capability using the quantitative area validation metric

Transactions of the American Nuclear Society, 118, 423–426. http://www.scopus.com/inward/record.url?eid=2-s2.0-85062957450&partnerID=MN8TOARS

Inverse uncertainty quantification of TRACE physical model parameters using sparse gird stochastic collocation surrogate model

Nuclear Engineering and Design, 319, 185–200.

Inverse uncertainty quantification of reactor simulations under the Bayesian framework using surrogate models constructed by polynomial chaos expansion

Nuclear Engineering and Design, 313, 29–52.

Kriging-based inverse uncertainty quantification of BISON fission gas release model

Transactions of the American Nuclear Society, 116, 629–632. http://www.scopus.com/inward/record.url?eid=2-s2.0-85033468956&partnerID=MN8TOARS

Sensitivity and uncertainty analysis of TRACE Physical Model Parameters based on PSBT benchmark using Gaussian process emulator

17th International Topical Meeting on Nuclear Reactor Thermal Hydraulics, NURETH 2017, 2017-September. http://www.scopus.com/inward/record.url?eid=2-s2.0-85051935457&partnerID=MN8TOARS

Surrogate-based inverse uncertainty quantification of TRACE physical model parameters using steady-state PSBT void fraction data

17th International Topical Meeting on Nuclear Reactor Thermal Hydraulics, NURETH 2017, 2017-September. http://www.scopus.com/inward/record.url?eid=2-s2.0-85051987392&partnerID=MN8TOARS

Coupling of system thermal-hydraulics and Monte-Carlo code: Convergence criteria and quantification of correlation between statistical uncertainty and coupled error

Annals of Nuclear Energy, 75, 377–387.

Evaluation of accident tolerant FeCrAl coating for PWR cladding under normal operating conditions with coupled neutron transport and fuel performance

Mathematics and Computations, Supercomputing in Nuclear Applications and Monte Carlo International Conference, M and C+SNA+MC 2015, 3, 2334–2344. http://www.scopus.com/inward/record.url?eid=2-s2.0-84949522107&partnerID=MN8TOARS

Neutronics and fuel performance evaluation of accident tolerant FeCrAl cladding under normal operation conditions

Annals of Nuclear Energy, 85, 763–775.

Coupling of system thermal-hydraulics and monte-carlo method for a consistent thermal-hydraulics-reactor physics feedback

International Congress on Advances in Nuclear Power Plants, ICAPP 2014, 2, 1164–1174. http://www.scopus.com/inward/record.url?eid=2-s2.0-84907077778&partnerID=MN8TOARS

Neutronics analysis of improved accident tolerance LWR fuel by modifing Zircaloy cladding of fuel pins

International Congress on Advances in Nuclear Power Plants, ICAPP 2014, 1, 159–166. http://www.scopus.com/inward/record.url?eid=2-s2.0-84907085456&partnerID=MN8TOARS

Neutronics and Fuel Performance Evaluation of Accident Tolerant Fuel under Normal Operation Conditions

Uncertainty quantification for coupled Monte Carlo and thermal-hydraulics codes

Transactions of the American Nuclear Society, 110, 189–191. http://www.scopus.com/inward/record.url?eid=2-s2.0-84904692027&partnerID=MN8TOARS

Engineered Zircaloy cladding modifications for improved accident tolerance of LWR fuel: A summary

LWR Fuel Performance Meeting, Top Fuel 2013, 1, 56–58. http://www.scopus.com/inward/record.url?eid=2-s2.0-84902344678&partnerID=MN8TOARS