Aidan Furlong

Furlong, A., Alsafadi, F., Palmtag, S., Godfrey, A., & Wu, X. (2025). Data-driven prediction and uncertainty quantification of PWR crud-induced power shift using convolutional neural networks. ENERGY, 316. https://doi.org/10.1016/j.energy.2025.134447

Akins, A., Furlong, A., Kohler, L., Clifford, J., Brady, C., Alsafadi, F., & Wu, X. (2024). ARTISANS-Artificial Intelligence for Simulation of Advanced Nuclear Systems for Nuclear Fission Technology. NUCLEAR ENGINEERING AND DESIGN, 423. https://doi.org/10.1016/j.nucengdes.2024.113170

Furlong, A., & Watson, J. (2024). Analysis of the LatticeNet neural network framework’s performance using prediction-calculated temperature coefficients in PWR assemblies. Annals of Nuclear Energy. https://doi.org/10.1016/j.anucene.2024.110498

Furlong, A., Watson, J., & Shriver, F. (2023). Investigation of Monte Carlo trained CNNs for neutronics predictions of typical and atypical PWR assemblies. Progress in Nuclear Energy, 166. https://doi.org/10.1016/j.pnucene.2023.104961

Furlong, A., Alsafadi, F., Kohler, L., Wu, X., Palmtag, S., Godfrey, A., & Hayes, S. (2023). Machine Learning-based Prediction of Crud Buildup Locations in Pressurized Water Reactors. Transactions of the American Nuclear Society, 129, 456–459. https://doi.org/10.13182/T129-42733

Predicting PWR Fuel Assembly CIPS Susceptibility with Convolutional Neural Networks: Performance and Uncertainty Quantification. (2024). International Conference on Physics of Reactors (PHYSOR 2024).

Prediction of CIPS Susceptibility in PWR Assemblies Using 3D Convolutional Neural Networks. (2024). Retrieved from https://www.lib.ncsu.edu/resolver/1840.20/41647

Furlong, A., Shriver, F., & Watson, J. K. (2022). Using Neural Networks to Predict Pin Powers in Reflective PWR Fuel Assemblies with Varying Pin Size. International Conference on Physics of Reactors 2022, 15–20,