Filter Results
Related Organization
- Biological and Environmental Systems Science Directorate (29)
- Computing and Computational Sciences Directorate (39)
- Energy Science and Technology Directorate
(229)
- Fusion and Fission Energy and Science Directorate (24)
- Information Technology Services Directorate (3)
- Isotope Science and Enrichment Directorate (7)
- National Security Sciences Directorate (20)
- Neutron Sciences Directorate (11)
- Physical Sciences Directorate (138)
- User Facilities (28)
Researcher
- Venkatakrishnan Singanallur Vaidyanathan
- Amir K Ziabari
- Philip Bingham
- Ryan Dehoff
- Vincent Paquit
- Dali Wang
- Diana E Hun
- Gina Accawi
- Gurneesh Jatana
- Huixin (anna) Jiang
- Jamieson Brechtl
- Jian Chen
- Kai Li
- Kashif Nawaz
- Mark M Root
- Michael Kirka
- Obaid Rahman
- Philip Boudreaux
- Wei Zhang
- Xiaobing Liu
- Zhili Feng

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.

This invention is directed to a machine leaning methodology to quantify the association of a set of input variables to a set of output variables, specifically for the one-to-many scenarios in which the output exhibits a range of variations under the same replicated input condi

Moisture management accounts for over 40% of the energy used by buildings. As such development of energy efficient and resilient dehumidification technologies are critical to decarbonize the building energy sector.

Simurgh revolutionizes industrial CT imaging with AI, enhancing speed and accuracy in nondestructive testing for complex parts, reducing costs.