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
- Peeyush Nandwana
- Brian Post
- Rangasayee Kannan
- Sudarsanam Babu
- Yong Chae Lim
- Zhili Feng
- Amit Shyam
- Blane Fillingim
- Jian Chen
- Lauren Heinrich
- Ryan Dehoff
- Thomas Feldhausen
- Wei Zhang
- Yousub Lee
- Adam Stevens
- Alexander Enders
- Alexander I Wiechert
- Alex Plotkowski
- Andres Marquez Rossy
- Benjamin Manard
- Bruce A Pint
- Bryan Lim
- Charles F Weber
- Christopher Fancher
- Christopher S Blessinger
- Costas Tsouris
- Dali Wang
- Gordon Robertson
- Govindarajan Muralidharan
- Isaac Sikkema
- Jay Reynolds
- Jeff Brookins
- Jiheon Jun
- Joanna Mcfarlane
- Jonathan Willocks
- Joseph Olatt
- Junghyun Bae
- Kunal Mondal
- Mahim Mathur
- Matt Vick
- Mingyan Li
- Oscar Martinez
- Peter Wang
- Priyanshi Agrawal
- Roger G Miller
- Rose Montgomery
- Sam Hollifield
- Sarah Graham
- Steven J Zinkle
- Thomas R Muth
- Tim Graening Seibert
- Tomas Grejtak
- Vandana Rallabandi
- Venugopal K Varma
- Weicheng Zhong
- Wei Tang
- William Peter
- Xiang Chen
- Yanli Wang
- Ying Yang
- Yiyu Wang
- Yukinori Yamamoto
- Yutai Kato

High-gradient magnetic filtration (HGMF) is a non-destructive separation technique that captures magnetic constituents from a matrix containing other non-magnetic species. One characteristic that actinide metals share across much of the group is that they are magnetic.

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

The lattice collimator places a grid of shielding material in front of a radiation detector to reduce the effect of background from surrounding materials and to enhance the RPM sensitivity to point sources rather than distributed sources that are commonly associated with Natur

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

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.

This work seeks to alter the interface condition through thermal history modification, deposition energy density, and interface surface preparation to prevent interface cracking.

Additive manufacturing (AM) enables the incremental buildup of monolithic components with a variety of materials, and material deposition locations.

The first wall and blanket of a fusion energy reactor must maintain structural integrity and performance over long operational periods under neutron irradiation and minimize long-lived radioactive waste.