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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.
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.
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.
Misalignment issues of the PWPT system have been addressed. The intercell power transformer has been introduced in order to improve load sharing of the system during a mismatch of the primary single-phase coil and the secondary multi-phase coils.
We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.
The incorporation of low embodied carbon building materials in the enclosure is increasing the fuel load for fire, increasing the demand for fire/flame retardants.
An ORNL invention proposes using 3D printing to make conductors with space-filling thin-wall cross sections. Space-filling thin-wall profiles will maximize the conductor volume while restricting the path for eddy currents induction.
The traditional window installation process involves many steps. These are becoming even more complex with newer construction requirements such as installation of windows over exterior continuous insulation walls.