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Researcher
- Singanallur Venkatakrishnan
- Amir K Ziabari
- Diana E Hun
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- Ryan Dehoff
- Stephen M Killough
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- Yaosuo Xue
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- Sreenivasa Jaldanki
- Suman Debnath
- Sunil Subedi
- Thomas Butcher
- Tyler Gerczak
- Yonghao Gui

ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.

A pressure burst feature has been designed and demonstrated for relieving potentially hazardous excess pressure within irradiation capsules used in the ORNL High Flux Isotope Reactor (HFIR).

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

Sintering additives to improve densification and microstructure control of UN provides a facile approach to producing high quality nuclear fuels.

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

This invention utilizes new techniques in machine learning to accelerate the training of ML-based communication receivers.

The use of Fluidized Bed Chemical Vapor Deposition to coat particles or fibers is inherently slow and capital intensive, as it requires constant modifications to the equipment to account for changes in the characteristics of the substrates to be coated.

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.