1 - 9 of 9 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.
Water heaters and heating, ventilation, and air conditioning (HVAC) systems collectively consume about 58% of home energy use.
Sensing of additive manufacturing processes promises to facilitate detailed quality inspection at scales that have seldom been seen in traditional manufacturing processes.
MAPSTER is a lightweight software package that automatically searches deployed laptops for geospatial data and complies metadata (GPS coordinates, file size, etc) at a central checkpoint.
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.