Journal Publications
Furlong, A., Watson, J. K., Shriver, F., “Investigation of Monte Carlo trained CNNs for neutronics predictions of typical and atypical PWR assemblies,” Progress in Nuclear Energy, Vol. 166, 104961, November (2023)
Smola, T., Watson, J. K., Hancock, S., Westover, T., Yeh, H., Umholtz, J., “Integrated Thermohydraulic Transient Testing of Steam Extraction Loop System to Support Joint Electricity-Hydrogen Production Using Generic Boiling Water Reactor,” Progress in Nuclear Energy, Vol. 160, 104692, June (2023)
Shriver, F., Watson, J. K., “Physically Adversarial Thermal Hydraulics Evaluation of Deep Learning Models for Pressurized Water Reactors,” Progress in Nuclear Energy, doi:10.1016/j.pnucene.2022.104149 (2022)
Shriver, F., Watson, J. K., “Scaling Deep Learning for Whole-Core Reactor Simulation,” Progress in Nuclear Energy, doi:10.1016/j.pnucene.2022.104134 (2022)
Shriver, F., Gentry, C., Watson, J. K., “Prediction of Neutronics Parameters within a 2D Reflective PWR Assembly Using Deep Learning,” Nuclear Science and Engineering, Taylor & Francis, 0, 1-22 (2021)
Garrett, G., Watson, J. K., “Comparison of water, helium, and carbon dioxide as coolants for next generation power plants using TRACE”, Annals of Nuclear Energy, 2019, 126, pp 292-302
Huang, Y, Cannon, F. S., Gou, J., Watson, J. K., Mathews, J. P., “Atomistic Modeling insight into the Structure of Lignite-Based Activated Carbon, and Behavior of Benzene Sorption,” RSC Advances, 2016, 6, 56623-37
Wang, Chang’an, Watson, J. K., Louw, E., Mathews, J. P., ”A Construction Strategy for Atomistic Models of Coal Chars Capturing Stacking Diversity and Pore Size Distribution”, Energy & Fuels, 2015, 29(8), pp 4814-4826
Huang, Y., Cannon, F.S., Watson, J. K., Reznik, B., Mathews, J. P., “Activated Carbon Efficient Atomistic Model Construction that Depicts Experimentally-Determined Characteristics”, Carbon, 2015, 83, pp 1-14
Alvarez, Y. E., Moreno, B. M., Klein, M. T., Watson, J. K., Castro-Mareano, F., Mathews, J. P., “A Novel Simplification Approach for Large-Scale Structural Models of Coal: 3D Molecules to 2D Lattices. 3. Reactive Lattice Simulations”, Energy & Fuels, 2013, 27, 2915-2922
Ellis, M. S., Watson, J. K., Ivanov, K., “Progress in the Development of an Implicit Steady State Solution in the Coupled Code TRACE/PARCS”, Progress in Nuclear Energy, 66, pp 1-12, 2013
Watson, J. K., Ivanov, K. N., “Demonstration of Implicit Coupling of TRACE/PARCS Using Simplified One-Dimensional Problems”, Nuclear Technology, Vol 180, \#2, November 2012, 174-190
Alvarez, Y. E., Watson, J. C. K., Mathews, J. P., “A Novel Simplification Approach for Large-Scale Structural Models of Coal: 3D Molecules to 2D Lattices. 1. Lattice Creation”, Energy & Fuels, 2012, 26, 4938-45
Alvarez, Y. E., Watson, J. K., Pou, J. O., Mathews, J. P., “A Novel Simplification Approach for Large-Scale Structural Models of Coal: 3D Molecules to 2D Lattices. 2. Visualization Capabilities”, Energy \& Fuels, 2012, 26, 4946-52
Pou, J., Alvarez, Y. E., Watson, J. K., Pisupati, S., Mathews, J. P., “Co-primary thermolysis molecular modeling simulation of lignin and subbituminous coal via a reactive coarse-grained simplification”, Journal of Analytical and Applied Pyrolysis, 2012, 95, 101-11
Castro-Marcano, F., Winans, R. E., Chupas, P., Chapman, K., Calo, J. M., Watson, J. K., Mathews, J. P., “Fine Structure Evaluation of the Pair Distribution Function with Molecular Models of the Argonne Premium Coals”, Energy Fuels 2012, ASAP DOI 10.1021/ef300364e
Fernandez-Also, V., Watson, J. K., Vander Wal, R., Mathews, J. P., “Soot and char molecular representations generated directly from HRTEM lattice fringe images using Fringe3D”, Combustion & Flame, 2011, 158, (9), 1807-13
Watson, J. K., K. N. Ivanov, 2002, “Improved Cross Section Modeling Methodology for Coupled Three-Dimensional Transient Simulation”, Annals of Nuclear Energy 29, 937-966
Conference Proceedings
(Invited) Watson, J. K., “Digital Twin – Physics Modeling and ML/AI for Generation IV Reactors,” Panel 9 – Digital and Intelligent Technology Applications in Advanced NPPs, ICONE 29, Shenzhen, China, August 8-12 (2022)
(Invited) Watson, J. K., Shriver, F., Furlong, A. “Prediction of PWR Pin Powers using Convolutional Neutral Networks,” PHYSOR 2022 : Scientific Machine Learning for Nuclear Engineering Applications Workshop, Pittsburgh Pa, May 15-20 (2022)
Furlong, A., Shriver, F., Watson, J. K., “Using Neural Networks to Predict Pin Powers in Reflective PWR Fuel Assemblies with Varying Pin Size,” PHYSOR 2022, Pittsburgh Pa, May 15-20, (2022)
Furlong, A.U, Shriver, F.G, Watson, J. K., “Application of LatticeNet Deep Learning Architecture on Neutronics Predictions Using OpenMC,” ANS Student Conference, April 8-10, pp. 1-3 (2021)
Shriver, F., Lee, S., Hamilton, S., Vetter, J., Watson, J. K., “Enhancing Monte Carlo Proxy Applications on GPSs,” 2019 IEEE/ACM Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS), 2019, pp. 30-40, doi: 10.1109/PMBS49563.2019.00009