1 - 10 of 10 Results
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.
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.
Sensing of additive manufacturing processes promises to facilitate detailed quality inspection at scales that have seldom been seen in traditional manufacturing processes.
The technologies provide a coating method to produce corrosion resistant and electrically conductive coating layer on metallic bipolar plates for hydrogen fuel cell and hydrogen electrolyzer applications.
Welding high temperature and/or high strength materials for aerospace or automobile manufacturing is challenging.
An innovative low-cost system for in-situ monitoring of strain and temperature during directed energy deposition.
This innovative approach combines optical and spectral imaging data via machine learning to accurately predict cancer labels directly from tissue images.
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.