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Researcher
- Hongbin Sun
- Srikanth Yoginath
- Venkatakrishnan Singanallur Vaidyanathan
- Amir K Ziabari
- Diana E Hun
- James J Nutaro
- Philip Bingham
- Philip Boudreaux
- Prashant Jain
- Pratishtha Shukla
- Ryan Dehoff
- Stephen M Killough
- Sudip Seal
- Vincent Paquit
- Ali Passian
- Bryan Maldonado Puente
- Corey Cooke
- Gina Accawi
- Gurneesh Jatana
- Harper Jordan
- Ian Greenquist
- Ilias Belharouak
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- Joel Dawson
- John Holliman II
- Mark M Root
- Michael Kirka
- Nance Ericson
- Nate See
- Nithin Panicker
- Nolan Hayes
- Obaid Rahman
- Pablo Moriano Salazar
- Peter Wang
- Pradeep Ramuhalli
- Praveen Cheekatamarla
- Ruhul Amin
- Ryan Kerekes
- Sally Ghanem
- Thien D. Nguyen
- Varisara Tansakul
- Vishaldeep Sharma
- Vittorio Badalassi

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

In nuclear and industrial facilities, fine particles, including radioactive residues—can accumulate on the interior surfaces of ventilation ducts and equipment, posing serious safety and operational risks.

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.

The invention presented here addresses key challenges associated with counterfeit refrigerants by ensuring safety, maintaining system performance, supporting environmental compliance, and mitigating health and legal risks.

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

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.

Digital twins (DTs) have emerged as essential tools for monitoring, predicting, and optimizing physical systems by using real-time data.

Simulation cloning is a technique in which dynamically cloned simulations’ state spaces differ from their parent simulation due to intervening events.

Recent advances in magnetic fusion (tokamak) technology have attracted billions of dollars of investments in startups from venture capitals and corporations to develop devices demonstrating net energy gain in a self-heated burning plasma, such as SPARC (under construction) and