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- Venkatakrishnan Singanallur Vaidyanathan
- Amir K Ziabari
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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.

How fast is a vehicle traveling? For different reasons, this basic question is of interest to other motorists, insurance companies, law enforcement, traffic planners, and security personnel. Solutions to this measurement problem suffer from a number of constraints.

We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.

We developed and incorporated two innovative mPET/Cu and mPET/Al foils as current collectors in LIBs to enhance cell energy density under XFC conditions.

Measurements of grid voltage and current are essential for the optimal operation of the grid protection and control (P&C) systems.

The co-processing of cathode and composite electrolyte for solid state polymer batteries has been developed. A traditional uncalendared cathode of e.g.

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.

Technologies directed to a multi-port autonomous reconfigurable solar power plant are described.