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Ziyu Xie
Ziyu Xie
Phd Student in Nuclear Engineering, NCSU
Verified email at ncsu.edu
Title
Cited by
Cited by
Year
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
332021
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
122022
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
122021
Scalable inverse uncertainty quantification by hierarchical bayesian modeling and variational inference
C Wang, X Wu, Z Xie, T Kozlowski
Energies 16 (22), 7664, 2023
52023
Functional PCA and deep neural networks-based Bayesian inverse uncertainty quantification with transient experimental data
Z Xie, M Yaseen, X Wu
Computer Methods in Applied Mechanics and Engineering 420, 116721, 2024
12024
Uncertainty Quantification of Deep Neural Network Predictions for Time-dependent Responses with Functional PCA
M Yaseen, Z Xie, X Wu
In Proceedings of the 20th International Topical Meeting on Nuclear Reactor …, 2023
12023
A systematic approach for the adequacy analysis of a set of experimental databases: Application in the framework of the ATRIUM activity
J Baccou, T Glantz, A Ghione, L Sargentini, P Fillion, G Damblin, R Sueur, ...
Nuclear Engineering and Design 421, 113035, 2024
2024
Benchmarking FFTF LOFWOS Test# 13 using SAM code: Baseline model development and uncertainty quantification
Y Liu, T Mui, Z Xie, R Hu
Annals of Nuclear Energy 192, 110010, 2023
2023
Inverse uncertainty quantification of a MOOSE-based melt pool model for additive manufacturing
Z Xie, X Wu, W Jiang, C Wang
Proceedings of the international conference on mathematics and computational …, 2021
2021
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