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ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.
We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.
Measurements of grid voltage and current are essential for the optimal operation of the grid protection and control (P&C) systems.
No readily available public data exists for vehicle class and weight information that covers the entire U.S. highway network. The Travel Monitoring Analysis System, managed by the Federal Highway Administration covers only less than 1% of the US highway network.
This invention utilizes new techniques in machine learning to accelerate the training of ML-based communication receivers.
Multi-terminal DC (MTdc) systems based on high-voltage DC (HVDC) transmission technology is an upcoming concept. In such systems, either asymmetric monopole or bi-pole systems are generally employed. Such systems are not suitable for easy expansion.
Stability performance of interconnected power grids plays crucial roles on their secure operation to prevent cascading failure and blackout.
Pairing hybrid neural network modeling techniques with artificial intelligence, or AI, controls has resulted in a unique hybrid system that creates a smart solution for traffic-signal timing.
Technologies directed to a multi-port autonomous reconfigurable solar power plant are described.
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).