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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.
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.
Through the use of splicing methods, joining two different fiber types in the tow stage of the process enables great benefits to the strength of the material change.
Knowing the state of charge of lithium-ion batteries, used to power applications from electric vehicles to medical diagnostic equipment, is critical for long-term battery operation.
Simurgh revolutionizes industrial CT imaging with AI, enhancing speed and accuracy in nondestructive testing for complex parts, reducing costs.