Farah Alsafadi

Alsafadi, F., & Wu, X. (2023). Deep generative modeling-based data augmentation with demonstration using the BFBT benchmark void fraction datasets. NUCLEAR ENGINEERING AND DESIGN, 415. https://doi.org/10.1016/j.nucengdes.2023.112712

Abu Saleem, R. A., Alsafadi, F. R., & Al-Abidah, N. (2022). Effect of mesh refinement on the solution of the inverse uncertainty quantification problem for transient physics. PROGRESS IN NUCLEAR ENERGY, 152. https://doi.org/10.1016/j.pnucene.2022.104360

Wu, X., Xie, Z., Alsafadi, F., & Kozlowski, T. (2021). A comprehensive survey of inverse uncertainty quantification of physical model parameters in nuclear system thermal-hydraulics codes. NUCLEAR ENGINEERING AND DESIGN, 384. https://doi.org/10.1016/j.nucengdes.2021.111460

Xie, Z., Alsafadi, F., & Wu, X. (2021). 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. https://doi.org/10.1016/j.nucengdes.2021.111423