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A novel approach is presented herein to improve time to onset of natural convection stemming from fuel element porosity during a failure mode of a nuclear reactor.
This invention utilizes new techniques in machine learning to accelerate the training of ML-based communication receivers.
Current technology for heating, ventilation, and air conditioning (HVAC) and other uses such as vending machines rely on refrigerants that have high global warming potential (GWP).
Current fuel used in nuclear light water reactors that generate energy for the grid use a solid form of uranium that is heated and processed to form pellets.
Technologies for optimizing prefab retrofit panel installation using a real-time evaluator is described.