Justin Watson

Associate Professor University of Florida

  • Gainesville FL

Justin Watson is an expert in multiphysics modeling and simulation of nuclear reactor systems for terrestrial and space applications.

Contact

University of Florida

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Biography

Justin Watson is currently an associate professor of nuclear engineering in the Materials Science and Engineering Department. His primary area of research is multiphysics simulation for the design and safety analysis of nuclear reactors. He has over 20 years of experience in developing reactor safety codes and performing design basis and operational occurrence transient analysis. He has over 15 years of experience teaching college level courses.

Areas of Expertise

Nuclear Reactor Design
Nuclear Engineering
Nuclear Reactor Safety Analysis

Media Appearances

A New Era of Nuclear? The Potential of Gas Core Reactors

UF Department of Materials Science & Engineering  online

2025-04-11

As the demand for clean, high-efficiency energy grows, a research team led by Justin Watson, Ph.D., and Chris McDevitt, Ph.D., associate professors of nuclear engineering at the University of Florida, is exploring gas core nuclear reactors (GCRs). This next-generation reactor design could offer a safer and more efficient way to generate atomic power by replacing traditional solid fuel rods with gaseous uranium fuel.

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Articles

An assessment of UO2 and ATF concept fuel performance modeling demands against current experimental capabilities under LOCA conditions

ScienceDirect

Probert, et al.

2024-09-15

This paper compiles and digitizes the publicly reported data for integral loss of coolant accident (LOCA) testing so it can be used by both multiphysics modeling and simulation groups and experimental groups.

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Analysis of the LatticeNet neural network framework’s performance using prediction-calculated temperature coefficients in PWR assemblies

ScienceDirect

Furlong & Watson

2024-08-01

In this paper, the LatticeNet neural network framework is investigated as a method to predict Doppler and moderator temperature coefficients for Pressurized Water Reactor (PWR) fuel assemblies, as well as differential boron worth.

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Investigation of Monte Carlo trained CNNs for neutronics predictions of typical and atypical PWR assemblies

ScienceDirect

Furlong, et al.

2023-12-01

This paper investigates the performance of LatticeNet as well as the tools developed alongside when given Monte Carlo-generated inputs and assemblies of varying pin dimensions, assessing the network’s tolerance to training data uncertainty and atypical configurations.

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Media