{"id":733,"date":"2023-10-23T10:09:39","date_gmt":"2023-10-23T14:09:39","guid":{"rendered":"https:\/\/ne.ncsu.edu\/artisans\/?page_id=733"},"modified":"2026-03-13T19:01:29","modified_gmt":"2026-03-13T23:01:29","slug":"transactions","status":"publish","type":"page","link":"https:\/\/ne.ncsu.edu\/artisans\/publications\/transactions\/","title":{"rendered":"Transactions"},"content":{"rendered":"\n
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Journals<\/a><\/div>\n\n\n\n
Conferences<\/a><\/div>\n\n\n\n
Transactions<\/a><\/div>\n<\/div>\n\n\n\n

Refereed Conference Transactions and Summaries<\/strong><\/mark><\/h4>\n\n\n\n
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  1. Akins, A. and Wu, X. (2026). Physics-Informed Diffusion Model for Generation of Physically Consistent Critical Heat Flux Data. In Transactions of American Nuclear Society. Denver, CO, USA, May 31 – June 3, 2026<\/li>\n\n\n\n
  2. Furlong, A., Salko, R., Zhao, X., and Wu, X. (2026). Prediction of Critical Heat Flux in Rod Bundles Using Tube-Based Hybrid ML Models in CTF. In Transactions of American Nuclear Society. Denver, CO, USA, May 31 – June 3, 2026<\/li>\n\n\n\n
  3. Clifford, J., Wu, X., Heifetz, A., and Kultgen, D. (2026). Verification Methods for Deploying Trustworthy Large Language Model Systems in Nuclear Operations and Maintenance. In Transactions of American Nuclear Society Student Conference. College Station, TX, USA, April 16 – 18, 2026<\/li>\n\n\n\n
  4. Miles, M., Clifford, J., Mikouchi-Lopez, J., Hou, J., and Wu, X. (2026). CORA: GraphRAG\/Neo4J-Powered Cognitive Operator Reactor Assistant. In Transactions of AmericanNuclear Society Student Conference. College Station, TX, USA, April 16 – 18, 2026<\/li>\n\n\n\n
  5. Furlong, A., Zhao, X., Salko, R., and Wu, X. (2025). Development and Deployment of Hybrid ML Models for Critical Heat Flux Prediction in Annulus Geometries. In Transactions of American Nuclear Society. Washington, DC, USA, November 9-12, 2025<\/li>\n\n\n\n
  6. Furlong, A., Zhao, X., Salko, R., and Wu, X. (2025). Native Fortran Implementation of TensorFlow-Trained Deep and Bayesian Neural Networks. In Transactions of American Nuclear Society. Chicago, IL, USA, June 15-18, 2025<\/li>\n\n\n\n
  7. Clifford, J., Kohler, L., White, J., Karim, N., Kautz, E., and Wu, X. (2025). Automating Spectroscopic Analysis of Lithium Isotopic Composition with Convolutional Neural Networks. In Transactions of the 2025 ANS Student Conference. Albuquerque, New Mexico, USA, April 3-5, 2025<\/li>\n\n\n\n
  8. Sadek, A., Yaseen, M., Ercanbrack, S., Ramzy Altahhan, M., Wu, X., and Ivanov, K. (2024). Evaluating the Uncertainty Effects of Carbon Nuclear Data on Pebble Bed Reactor Physics: A Comparative Study of ENDF\/B-VII.1 and ENDF\/B-VIII.0. In Transactions of American Nuclear Society. Orlando, FL, USA, November 17-21, 2024<\/li>\n\n\n\n
  9. 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<\/li>\n\n\n\n
  10. 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<\/li>\n\n\n\n
  11. 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<\/li>\n\n\n\n
  12. 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<\/li>\n\n\n\n
  13. 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<\/li>\n\n\n\n
  14. 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<\/li>\n\n\n\n
  15. 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<\/li>\n\n\n\n
  16. 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\u201316, 2022 <\/li>\n\n\n\n
  17. 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\u201316, 2022<\/li>\n\n\n\n
  18. Alsafadi, F. and Wu, X. (2022). Data Augmentation with Generative Adversarial Networks. In Transactions of American Nuclear Society. Anaheim, CA, USA, June 12\u201316, 2022<\/li>\n\n\n\n
  19. 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\u201316, 2022<\/li>\n\n\n\n
  20. 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<\/li>\n\n\n\n
  21. 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<\/li>\n\n\n\n
  22. 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<\/li>\n\n\n\n
  23. 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<\/li>\n\n\n\n
  24. 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<\/li>\n\n\n\n
  25. 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<\/li>\n\n\n\n
  26. 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<\/li>\n\n\n\n
  27. 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<\/li>\n\n\n\n
  28. 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<\/li>\n\n\n\n
  29. 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<\/li>\n\n\n\n
  30. 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<\/li>\n\n\n\n
  31. 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<\/li>\n\n\n\n
  32. 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<\/li>\n<\/ol>\n\n\n\n

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