Transactions
Refereed Conference Transactions and Summaries
- Richards, W., Dahm, Z., Buss, O., Anghel, C., Moravej, K., Zhao, X., Foad, B. F., Rohatgi, U., Delipei, G., Wu, X., and Chatzidakis, S. (2024). Developing a Machine Learning Benchmark Using Real-Time Data from the PUR-1 Reactor for Nuclear Applications. In Transactions of American Nuclear Society. Las Vegas, NV, USA, June 16-19, 2024
- Kohler, L., Clifford, J., Karim, N., Harilal, S. S., Kautz, E., and Wu, X. (2024). ML-LIBS: Machine Learning-Based Spectra Predictions of Time-Dependent Lithium Emission Spectroscopy Imaging. In Transactions of the 2024 ANS Student Conference. University Park, Pennsylvania, USA, April 4-6, 2024
- Furlong, A., Alsafadi, F., Kohler, L., Wu, X., Palmtag, S., Godfrey, A., and Hayes, S. (2023). Machine Learning-based Prediction of Crud Buildup Locations in Pressurized Water Reactors. In Transactions of American Nuclear Society. Washington, D.C., USA, November 12-15, 2023
- Bolgova, D., Abarca, A., Wu, X., and Avramova, M. (2023). CANDU Fuel Channel Modeling in CTF Within the OECD-NEA Blind Benchmark on CANDU Thermal-Hydraulics. In Transactions of American Nuclear Society. Washington, D.C., USA, November 12-15, 2023
- Yushu, D., McMurtrey, M., Wu, X., Monson, A., and German, P. (2023). Directed Energy Deposition Process Modeling, Validation, and Process-Informed Optimization. In Proceedings of the 17th U. S. National Congress on Computational Mechanics (USNCCM). Albuquerque, New Mexico, USA, July 23-27, 2023
- Wu, X., Delipei, G., Avramova, M., and Ivanov, K. (2022). Introducing the OECD/NEA WPRS Task Force on Artificial Intelligence and Machine Learning. In Transactions of American Nuclear Society. Phoenix, AZ, USA, November 13-17, 2022
- Wu, X., Delipei, G., Avramova, M., and Ivanov, K. (2022). Why is Uncertainty Quantification Important for Machine Learning Models? In Transactions of American Nuclear Society. Phoenix, AZ, USA, November 13-17, 2022
- Zino, J. and Wu, X. (2022). A New Monte Carlo Course for Undergraduate Nuclear Engineering Students. In Transactions of American Nuclear Society. Anaheim, CA, USA, June 12–16, 2022
- Yaseen, M. and Wu, X. (2022). How to Quantify Approximation Uncertainties of Deep Neural Networks? In Transactions of American Nuclear Society. Anaheim, CA, USA, June 12–16, 2022
- Alsafadi, F. and Wu, X. (2022). Data Augmentation with Generative Adversarial Networks. In Transactions of American Nuclear Society. Anaheim, CA, USA, June 12–16, 2022
- Wu, X. (2022). Development of a New Course on Scientific Machine Learning in a Nuclear Engineering Department. In Transactions of American Nuclear Society. Anaheim, CA, USA, June 12–16, 2022
- Alsafadi, F., Xie, Z., and Wu, X. (2021). Quantitative Validation with Bayes Factor. In Transactions of American Nuclear Society. Washington, DC, USA, Nov. 30 – Dec. 4, 2021
- Akins, A., Xie, Z., and Wu, X. (2021). Solving a System of Ordinary Differential Equations for Reactivity Insertion Accident with Artificial Neural Networks. In Transactions of American Nuclear Society. Washington, DC, USA, Nov. 30 – Dec. 4, 2021
- Jin, Y., Wu, X., and Shirvan, K. (2019). TRACE Simulation of a BWR Large Break LOCA with Zircaloy and Cr-Coated Cladding. In Transactions of American Nuclear Society. Washington, DC, USA, Nov. 17-21, 2019
- Wu, X. and Shirvan, K. (2018). System Code Evaluation of Accident Tolerant Claddings during BWR Station Blackout Accident. In Transactions of American Nuclear Society. Orlando, FL, USA, Nov. 11-15, 2018
- Che, Y., Wu, X., Pastore, G., Hales, J., and Shirvan, K. (2018). Sensitivity and Uncertainty Analysis for Fuel Performance Evaluation of Cr2O3-doped UO2 Fuel under LB-LOCA. In Transactions of American Nuclear Society. Orlando, FL, USA, Nov. 11-15, 2018
- Wu, X., Shirvan, K., and Kozlowski, T. (2018). Validating TRACE Void Fraction Predictive Capability using the Quantitative Area Validation Metric. In Transactions of American Nuclear Society. Philadelphia, PA, USA, June 17-21, 2018
- Wu, X., Shirvan, K., and Kozlowski, T. (2018). On the Connection between Sensitivity and Identifiability for Inverse Uncertainty Quantification. In Transactions of American Nuclear Society. Philadelphia, PA, USA, June 17-21, 2018
- Wang, C., Wu, X., Borowiec, K., and Kozlowski, T. (2018). Bayesian Calibration and Uncertainty Quantification for TRACE Based on PSBT Benchmark. In Transactions of American Nuclear Society. Philadelphia, PA, USA, June 17-21, 2018
- Wu, X. and Kozlowski, T. (2017). Inverse Uncertainty Quantification of TRACE Physical Model Parameters with Model Discrepancy. In Transactions of American Nuclear Society. Washington, DC, USA, Oct. 29 – Nov. 2, 2017
- Wu, X. and Kozlowski, T. (2017). Metamodel-based Inverse Uncertainty Quantification of TRACE Physical Model Parameters. In ASME Verification and Validation Symposium (VVS-2017). Las Vegas, NV, USA, May 3-5, 2017
- Wu, X. and Kozlowski, T. (2017). Kriging-based Inverse Uncertainty Quantification of BISON Fission Gas Release Model. In Transactions of American Nuclear Society. San Francisco, CA, USA, June 11-15, 2017
- Wu, X. and Kozlowski, T. (2016). Inverse Uncertainty Quantification of Reactor Simulation with Polynomial Chaos Surrogate Model. In Transactions of American Nuclear Society. New Orleans, LA, USA, June 12-16, 2016
- Wu, X. and Kozlowski, T. (2014). Uncertainty Quantification for Coupled Monte Carlo and Thermal-Hydraulics Codes. In Transactions of American Nuclear Society. Reno, NV, USA, June 15-19, 2014