Dr. Xu Wu is an Assistant Professor at the Department of Nuclear Engineering of the North Carolina State University. his research interests include: (1) Calibration, Validation, Data Assimilation, Uncertainty and Sensitivity Analysis; (2) Computational Statistics, Reduced Order Modeling, Bayesian Inference and Model Inversion; (3) mathematical representations of model discrepancy to improve model predictive capabilities; (4) Physics-Informed Machine Learning, Deep Learning; (5) System Thermal-Hydraulics, Nuclear Fuel Performance Modeling, Multi-physics Coupled Simulation; (6) Accident Tolerant Fuels (ATFs) modeling, etc.

Works (30)

Updated: April 21st, 2023 07:05

2023 journal article

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

ANNALS OF NUCLEAR ENERGY, 188.

By: L. Moloko, P. Bokov, X. Wu & K. Ivanov

author keywords: Uncertainty quantification; Deep neural networks; Bayesian Neural Networks; Monte Carlo dropout
Sources: ORCID, Web Of Science
Added: March 23, 2023

2022 journal article

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

ANNALS OF NUCLEAR ENERGY, 165.

By: Z. Xie, W. Jiang*, C. Wang* & X. Wu

author keywords: Inverse uncertainty quantification; Melt pool; Additive manufacturing
Sources: Web Of Science, ORCID
Added: November 29, 2021

2022 article

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.

By: M. Yaseen & X. Wu

author keywords: Uncertainty quantification; Deep Neural Network; Monte Carlo Dropout; Deep Ensemble; Bayesian Neural Network
Sources: ORCID, Web Of Science
Added: November 3, 2022

2021 journal article

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

NUCLEAR ENGINEERING AND DESIGN, 384.

author keywords: Inverse uncertainty quantification; Calibration; Physical model parameters; Frequentist; Bayesian; Empirical
Sources: Web Of Science, ORCID
Added: November 1, 2021

2021 journal article

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

ANNALS OF NUCLEAR ENERGY, 153.

By: Y. Che*, X. Wu, G. Pastore*, W. Li* & K. Shirvan*

author keywords: Doped fuel; Variational Bayesian Monte Carlo (VBMC); Bayesian inference; Kriging; Principal Component Analysis (PCA)
Sources: Web Of Science, ORCID
Added: February 15, 2021

2021 journal article

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

Nuclear Technology, 10, 1–19.

By: C. Lu, Z. Wu* & X. Wu

author keywords: Thermal stratification; sodium-cooled fast reactor; sensitivity analysis; inverse uncertainty quantification
Source: ORCID
Added: October 17, 2020

2021 journal article

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.

By: Z. Xie, F. Alsafadi & X. Wu

author keywords: Inverse Uncertainty Quantification; Quantitative validation; Bayesian hypothesis testing; Bayes factor; ANS nuclear grand challenge
Sources: Web Of Science, ORCID
Added: October 12, 2021

2020 journal article

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

NUCLEAR ENGINEERING AND DESIGN, 368.

By: Y. Jin*, X. Wu & K. Shirvan*

author keywords: Accident Tolerant Fuel; FeCrAl; Cr-coating; Station Blackout
Sources: Web Of Science, ORCID
Added: November 2, 2020

2019 journal article

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

Journal of Computational Physics, 396, 12–30.

By: X. Wu, K. Shirvan* & T. Kozlowski*

author keywords: Inverse uncertainty quantification; Modular Bayesian approach; Identifiability; Sensitivity
Source: ORCID
Added: July 5, 2019

2019 journal article

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.

By: C. Wang*, X. Wu & T. Kozlowski*

author keywords: Inverse uncertainty quantification; Gaussian process; physical model parameter uncertainty; PSBT benchmark
Source: ORCID
Added: July 5, 2019

2018 conference paper

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

By: C. Wang, X. Wu, K. Borowiec & T. Kozlowski

Source: ORCID
Added: July 5, 2019

2018 journal article

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

Nuclear Engineering and Design, 335, 417–431.

author keywords: Inverse uncertainty quantification; Bayesian calibration; Gaussian Process; Modular Bayesian; Model discrepancy
Source: ORCID
Added: July 5, 2019

2018 journal article

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

Nuclear Engineering and Design, 335, 339–355.

By: X. Wu, T. Kozlowski*, H. Meidani* & K. Shirvan*

author keywords: Inverse uncertainty quantification; Bayesian calibration; Gaussian process; Modular Bayesian; Model discrepancy
Source: ORCID
Added: July 5, 2019

2018 journal article

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.

author keywords: Inverse uncertainty quantification; Metamodel; Kriging; Nuclear fuel performance analysis; Principal component analysis
Source: ORCID
Added: July 5, 2019

2018 conference paper

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

By: X. Wu, K. Shirvan & T. Kozlowski

Source: ORCID
Added: July 5, 2019

2018 conference paper

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

By: Y. Che, X. Wu, G. Pastore, J. Hales & K. Shirvan

Source: ORCID
Added: July 5, 2019

2018 conference paper

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

By: X. Wu & K. Shirvan

Source: ORCID
Added: July 5, 2019

2018 conference paper

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

By: X. Wu, K. Shirvan & T. Kozlowski

Source: ORCID
Added: July 5, 2019

2017 journal article

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

Nuclear Engineering and Design, 319, 185–200.

By: X. Wu, T. Mui*, G. Hu*, H. Meidani* & T. Kozlowski*

Source: ORCID
Added: July 5, 2019

2017 journal article

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.

By: X. Wu & T. Kozlowski*

Source: ORCID
Added: July 5, 2019

2017 conference paper

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

By: X. Wu & T. Kozlowski

Source: ORCID
Added: July 5, 2019

2017 conference paper

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

By: C. Wang, X. Wu & T. Kozlowski

Source: ORCID
Added: July 5, 2019

2017 conference paper

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

By: C. Wang, X. Wu & T. Kozlowski

Source: ORCID
Added: July 5, 2019

2015 journal article

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.

By: X. Wu & T. Kozlowski*

author keywords: Monte Carlo; System thermal-hydraulics; Coupled simulation; Uncertainty quantification
Source: ORCID
Added: July 5, 2019

2015 conference paper

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

By: M. Rose, T. Downar, X. Wu & T. Kozlowski

Source: ORCID
Added: July 5, 2019

2015 journal article

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

Annals of Nuclear Energy, 85, 763–775.

By: X. Wu, T. Kozlowski* & J. Hales*

author keywords: FeCrAl; Accident Tolerant Fuel
Source: ORCID
Added: July 5, 2019

2014 conference paper

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

By: X. Wu & T. Kozlowski

Source: ORCID
Added: July 5, 2019

2014 conference paper

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

By: X. Wu, T. Kozlowski & B. Heuser

Source: ORCID
Added: July 5, 2019

2014 conference paper

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

By: X. Wu & T. Kozlowski

Source: ORCID
Added: July 5, 2019

2013 conference paper

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

By: B. Heuser, T. Kozlowski & W. Xu

Source: ORCID
Added: July 5, 2019

Employment

Updated: June 29th, 2019 11:25

2019 - present

North Carolina State University Raleigh, NC, US
Assistant Professor Department of Nuclear Engineering

2017 - 2019

Massachusetts Institute of Technology Cambridge, MA, US
Postdoctoral Associate Department of Nuclear Science and Engineering

Education

Updated: October 11th, 2019 14:14

2013 - 2017

University of Illinois at Urbana-Champaign Urbana, IL, US
Ph.D Department of Nuclear, Plasma and Radiological Engineering

2011 - 2013

University of Illinois at Urbana-Champaign Urbana, IL, US
M.S. in Nuclear Engineering Department of Nuclear, Plasma and Radiological Engineering

2007 - 2011

Shanghai Jiao Tong University Shanghai, CN
B.S in Nuclear Engineering and Technology School of Mechanical Engineering