| 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 | 48 | 2021 |
| 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 | 14 | 2021 |
| Deep generative modeling-based data augmentation with demonstration using the BFBT benchmark void fraction datasets F Alsafadi, X Wu Nuclear Engineering and Design 415, 112712, 2023 | 7 | 2023 |
| Development of Whole System Digital Twins for Advanced Reactors: Leveraging Graph Neural Networks and SAM Simulations Y Liu, F Alsafadi, T Mui, D O’Grady, R Hu Nuclear Technology, 1-18, 2024 | 3 | 2024 |
| Predicting Critical Heat Flux with Uncertainty Quantification and Domain Generalization Using Conditional Variational Autoencoders and Deep Neural Networks F Alsafadi, A Furlong, X Wu arXiv preprint arXiv:2409.05790, 2024 | 3 | 2024 |
| ARTISANS—Artificial Intelligence for Simulation of Advanced Nuclear Systems for Nuclear Fission Technology A Akins, A Furlong, L Kohler, J Clifford, C Brady, F Alsafadi, X Wu Nuclear Engineering and Design 423, 113170, 2024 | 1 | 2024 |
| Predicting pwr fuel assembly cips susceptibility with convolutional neural networks: Performance and uncertainty quantification A Furlong, F Alsafadi, S Palmtag, A Godfrey, S Hayes, X Wu 2024 International Conference on Physics of Reactors, PHYSOR 2024, 1684-1693, 2024 | 1 | 2024 |
| Machine learning-based prediction of crud buildup locations in pressurized water reactors A Furlong, F Alsafadi, L Kohler, X Wu, S Palmtag, A Godfrey, S Hayes Transactions of the American Nuclear Society 129, 456-459, 2023 | 1 | 2023 |
| Effect of mesh refinement on the solution of the inverse uncertainty quantification problem for transient physics RAA Saleem, FR Alsafadi, N Al-Abidah Progress in Nuclear Energy 152, 104360, 2022 | 1 | 2022 |
| Data-driven prediction and uncertainty quantification of PWR Crud-Induced Power Shift using convolutional neural networks A Furlong, F Alsafadi, S Palmtag, A Godfrey, X Wu Energy, 134447, 2025 | | 2025 |
| An Investigation on Machine Learning Predictive Accuracy Improvement and Uncertainty Reduction using VAE-based Data Augmentation F Alsafadi, M Yaseen, X Wu arXiv preprint arXiv:2410.19063, 2024 | | 2024 |
| EFFECT OF PARAMETRIC TUNING ON THE SOLUTION OF THE INVERSE UNCERTAINTY QUANTIFICATION PROBLEM FR AL-SAFADI Jordan University of Science and Technology, 2020 | | 2020 |
Xu WuAssistant Professor of Nuclear Engineering, North Carolina State UniversityPreverjeni e-poštni naslov na ncsu.edu
