1 - 10 of 11 Results
ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.
System and method for part porosity monitoring of additively manufactured components using machining
In additive manufacturing, choice of process parameters for a given material and geometry can result in porosities in the build volume, which can result in scrap.
We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.
Sensing of additive manufacturing processes promises to facilitate detailed quality inspection at scales that have seldom been seen in traditional manufacturing processes.
This technology is a laser-based heating unit that offers rapid heating profiles on a research scale with minimal incidental heating of materials processing environments.
A novel molecular sorbent system for low energy CO2 regeneration is developed by employing CO2-responsive molecules and salt in aqueous media where a precipitating CO2--salt fractal network is formed, resulting in solid-phase formation and sedimentation.
Simurgh revolutionizes industrial CT imaging with AI, enhancing speed and accuracy in nondestructive testing for complex parts, reducing costs.
An innovative low-cost system for in-situ monitoring of strain and temperature during directed energy deposition.
This invention is about a multifunctional structured packing device that can simultaneously facilitate heat and mass transfer in packed distillation, absorption, and liquid extraction columns, as well as in multiphase reactors.