Filter Results
Related Organization
- Biological and Environmental Systems Science Directorate (23)
- Computing and Computational Sciences Directorate (35)
- Energy Science and Technology Directorate (217)
- Fusion and Fission Energy and Science Directorate (21)
- Information Technology Services Directorate (2)
- Isotope Science and Enrichment Directorate (6)
- National Security Sciences Directorate (17)
- Neutron Sciences Directorate (11)
- Physical Sciences Directorate (128)
- User Facilities (27)
Researcher
- Ryan Dehoff
- Singanallur Venkatakrishnan
- Srikanth Yoginath
- William Carter
- Alex Roschli
- Amir K Ziabari
- Andrzej Nycz
- Brian Post
- Chris Masuo
- James J Nutaro
- Luke Meyer
- Philip Bingham
- Pratishtha Shukla
- Sudip Seal
- Vincent Paquit
- Adam Stevens
- Alex Walters
- Ali Passian
- Amy Elliott
- Cameron Adkins
- Diana E Hun
- Erin Webb
- Evin Carter
- Gina Accawi
- Gurneesh Jatana
- Harper Jordan
- Isha Bhandari
- Jeremy Malmstead
- Joel Asiamah
- Joel Dawson
- Joshua Vaughan
- Kitty K Mccracken
- Liam White
- Mark M Root
- Michael Borish
- Michael Kirka
- Nance Ericson
- Obaid Rahman
- Oluwafemi Oyedeji
- Pablo Moriano Salazar
- Peter Wang
- Philip Boudreaux
- Rangasayee Kannan
- Roger G Miller
- Sarah Graham
- Soydan Ozcan
- Sudarsanam Babu
- Tyler Smith
- Varisara Tansakul
- William Peter
- Xianhui Zhao
- Yukinori Yamamoto

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.

The use of biomass fiber reinforcement for polymer composite applications, like those in buildings or automotive, has expanded rapidly due to the low cost, high stiffness, and inherent renewability of these materials. Biomass are commonly disposed of as waste.

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.