Filter Results
Related Organization
- Biological and Environmental Systems Science Directorate (29)
- Computing and Computational Sciences Directorate (39)
- Energy Science and Technology Directorate (229)
- Fusion and Fission Energy and Science Directorate (24)
- Information Technology Services Directorate (3)
- Isotope Science and Enrichment Directorate (7)
- National Security Sciences Directorate (20)
- Neutron Sciences Directorate (11)
- Physical Sciences Directorate
(138)
- User Facilities (28)
Researcher
- Chris Tyler
- Amit Shyam
- Beth L Armstrong
- Justin West
- Peeyush Nandwana
- Brian Post
- Ritin Mathews
- Ying Yang
- Alex Plotkowski
- Jun Qu
- Rangasayee Kannan
- Ryan Dehoff
- Sudarsanam Babu
- Yong Chae Lim
- Zhili Feng
- Alice Perrin
- Blane Fillingim
- Christopher Ledford
- Corson Cramer
- David Olvera Trejo
- J.R. R Matheson
- James A Haynes
- Jaydeep Karandikar
- Jian Chen
- Lauren Heinrich
- Meghan Lamm
- Michael Kirka
- Scott Smith
- Steve Bullock
- Steven J Zinkle
- Sumit Bahl
- Thomas Feldhausen
- Tomas Grejtak
- Wei Zhang
- Yanli Wang
- Yousub Lee
- Yutai Kato
- Adam Stevens
- Akash Jag Prasad
- Andres Marquez Rossy
- Benjamin Lawrie
- Ben Lamm
- Brian Gibson
- Bruce A Pint
- Bryan Lim
- Calen Kimmell
- Chengyun Hua
- Christopher Fancher
- Costas Tsouris
- Dali Wang
- David J Mitchell
- David S Parker
- Dean T Pierce
- Emma Betters
- Ethan Self
- Gabor Halasz
- Gabriel Veith
- Gerry Knapp
- Glenn R Romanoski
- Gordon Robertson
- Govindarajan Muralidharan
- Greg Corson
- Gs Jung
- Gyoung Gug Jang
- James Klett
- Jay Reynolds
- Jeff Brookins
- Jesse Heineman
- Jiaqiang Yan
- Jiheon Jun
- John Potter
- Jong K Keum
- Jordan Wright
- Josh B Harbin
- Jovid Rakhmonov
- Khryslyn G Araño
- Marm Dixit
- Matthew S Chambers
- Mina Yoon
- Nancy Dudney
- Nicholas Richter
- Patxi Fernandez-Zelaia
- Peter Wang
- Petro Maksymovych
- Priyanshi Agrawal
- Radu Custelcean
- Roger G Miller
- Rose Montgomery
- Sarah Graham
- Sergiy Kalnaus
- Shajjad Chowdhury
- Sunyong Kwon
- Thomas R Muth
- Tim Graening Seibert
- Tolga Aytug
- Tony L Schmitz
- Trevor Aguirre
- Venugopal K Varma
- Vladimir Orlyanchik
- Weicheng Zhong
- Wei Tang
- William Peter
- Xiang Chen
- Yan-Ru Lin
- Yiyu Wang
- Yukinori Yamamoto

A finite element approach integrated with a novel constitute model to predict phase change, residual stresses and part deformation.

Currently available cast Al alloys are not suitable for various high-performance conductor applications, such as rotor, inverter, windings, busbar, heat exchangers/sinks, etc.

The invented alloys are a new family of Al-Mg alloys. This new family of Al-based alloys demonstrate an excellent ductility (10 ± 2 % elongation) despite the high content of impurities commonly observed in recycled aluminum.

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.

V-Cr-Ti alloys have been proposed as candidate structural materials in fusion reactor blanket concepts with operation temperatures greater than that for reduced activation ferritic martensitic steels (RAFMs).

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.

This invention is directed to a machine leaning methodology to quantify the association of a set of input variables to a set of output variables, specifically for the one-to-many scenarios in which the output exhibits a range of variations under the same replicated input condi

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.