1 - 10 of 23 Results
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.
The lack of real-time insights into how materials evolve during laser powder bed fusion has limited the adoption by inhibiting part qualification. The developed approach provides key data needed to fabricate born qualified parts.
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.
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.
This work seeks to alter the interface condition through thermal history modification, deposition energy density, and interface surface preparation to prevent interface cracking.
Additive manufacturing (AM) enables the incremental buildup of monolithic components with a variety of materials, and material deposition locations.
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.