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Optimized Configuration of Nuclear Reactor Fuel Rods
Neural Network Model Applies High-Fidelity Outcomes in Less Time This neural network architecture, LatticeNet, uses computer vision, modular neural networks, and deep learning approaches to optimize the fuel rod configuration in a nuclear reactor stack in the time it takes a low-fidelity application to do one run. Available applications in machine...
Published: 1/17/2023   |   Inventor(s): Justin Watson, Forrest Shriver, Cole Gentry
Keywords(s):  
Category(s): Technology Classifications > Engineering > Computer Science