Filter Results
Related Organization
- Biological and Environmental Systems Science Directorate (23)
- Computing and Computational Sciences Directorate (35)
- Energy Science and Technology Directorate (217)
- Fusion and Fission Energy and Science Directorate
(21)
- Information Technology Services Directorate (2)
- Isotope Science and Enrichment Directorate (6)
- National Security Sciences Directorate (17)
- Neutron Sciences Directorate (11)
- Physical Sciences Directorate
(128)
- User Facilities (27)
Researcher
- Chris Tyler
- Justin West
- Ritin Mathews
- Yong Chae Lim
- Brian Post
- David Olvera Trejo
- Hongbin Sun
- J.R. R Matheson
- Jaydeep Karandikar
- Prashant Jain
- Rangasayee Kannan
- Scott Smith
- Adam Stevens
- Akash Jag Prasad
- Brian Gibson
- Bryan Lim
- Calen Kimmell
- Emma Betters
- Greg Corson
- Ian Greenquist
- Ilias Belharouak
- Jesse Heineman
- Jiheon Jun
- John Potter
- Josh B Harbin
- Nate See
- Nithin Panicker
- Peeyush Nandwana
- Pradeep Ramuhalli
- Praveen Cheekatamarla
- Priyanshi Agrawal
- Roger G Miller
- Ruhul Amin
- Ryan Dehoff
- Sarah Graham
- Sudarsanam Babu
- Tomas Grejtak
- Tony L Schmitz
- Vishaldeep Sharma
- Vittorio Badalassi
- Vladimir Orlyanchik
- William Peter
- Yiyu Wang
- Yukinori Yamamoto
- Zhili Feng

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.

The invention presented here addresses key challenges associated with counterfeit refrigerants by ensuring safety, maintaining system performance, supporting environmental compliance, and mitigating health and legal risks.

Distortion generated during additive manufacturing of metallic components affect the build as well as the baseplate geometries. These distortions are significant enough to disqualify components for functional purposes.

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.

For additive manufacturing of large-scale parts, significant distortion can result from residual stresses during deposition and cooling. This can result in part scraps if the final part geometry is not contained in the additively manufactured preform.

A novel approach is presented herein to improve time to onset of natural convection stemming from fuel element porosity during a failure mode of a nuclear reactor.

In additive manufacturing large stresses are induced in the build plate and part interface. A result of these stresses are deformations in the build plate and final component.

Materials produced via additive manufacturing, or 3D printing, can experience significant residual stress, distortion and cracking, negatively impacting the manufacturing process.

Quantifying tool wear is historically challenging task due to variable human interpretation. This capture system will allow for an entire side and the complete end of the cutting tool to be analyzed.