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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.
We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.
A new nanostructured bainitic steel with accelerated kinetics for bainite formation at 200 C was designed using a coupled CALPHAD, machine learning, and data mining approach.
New demands in electric vehicles have resulted in design changes for the power electronic components such as the capacitor to incur lower volume, higher operating temperatures, and dielectric properties (high dielectric permittivity and high electrical breakdown strengths).
The first wall and blanket of a fusion energy reactor must maintain structural integrity and performance over long operational periods under neutron irradiation and minimize long-lived radioactive waste.
Simurgh revolutionizes industrial CT imaging with AI, enhancing speed and accuracy in nondestructive testing for complex parts, reducing costs.