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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 eDICEML digital twin is proposed which emulates networks and hosts of an instrument-computing ecosystem. It runs natively on an ecosystem’s host or as a portable virtual machine.
How fast is a vehicle traveling? For different reasons, this basic question is of interest to other motorists, insurance companies, law enforcement, traffic planners, and security personnel. Solutions to this measurement problem suffer from a number of constraints.
Here we present a solution for practically demonstrating path-aware routing and visualizing a self-driving network.
We’ve developed a more cost-effective cable driven robot system for installing prefabricated panelized building envelopes. Traditional cable robots use eight cables, which require extra support structures, making setup complex and expensive.
Currently available cast Al alloys are not suitable for various high-performance conductor applications, such as rotor, inverter, windings, busbar, heat exchangers/sinks, etc.
US coastal and island communities have vulnerable energy infrastructure and high energy costs, which are exacerbated by climate change.
The invented alloys are a new family of Al-Mg alloys. This new family of Al-based alloys demonstrate an excellent ductility (10 ± 2 % elongation) despite the high content of impurities commonly observed in recycled aluminum.
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.