1 - 10 of 19 Results
ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.
A pressure burst feature has been designed and demonstrated for relieving potentially hazardous excess pressure within irradiation capsules used in the ORNL High Flux Isotope Reactor (HFIR).
We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.
We present the design, assembly and demonstration of functionality for a new custom integrated robotics-based automated soil sampling technology as part of a larger vision for future edge computing- and AI- enabled bioenergy field monitoring and management technologies called
Red mud residue is an industrial waste product generated during the processing of bauxite ore to extract alumina for the steelmaking industry. Red mud is rich in minerals in bauxite like iron and aluminum oxide, but also heavy metals, including arsenic and mercury.
High strength, oxidation resistant refractory alloys are difficult to fabricate for commercial use in extreme environments.
This invention utilizes new techniques in machine learning to accelerate the training of ML-based communication receivers.
