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Researcher
- Brian Post
- Peter Wang
- Ryan Dehoff
- Andrzej Nycz
- Peeyush Nandwana
- Ahmed Hassen
- Blane Fillingim
- Chris Masuo
- Sudarsanam Babu
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- Yong Chae Lim
- Zhili Feng
- Amit Shyam
- J.R. R Matheson
- Jian Chen
- Joshua Vaughan
- Lauren Heinrich
- Michael Kirka
- Rangasayee Kannan
- Vincent Paquit
- Vlastimil Kunc
- Wei Zhang
- Yousub Lee
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- Brian Gibson
- Bryan Lim
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- Christopher Fancher
- Christopher Ledford
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- Clay Leach
- Craig Blue
- Dali Wang
- David Nuttall
- David Olvera Trejo
- Gordon Robertson
- Isha Bhandari
- James Haley
- Jay Reynolds
- Jeff Brookins
- Jesse Heineman
- Jiheon Jun
- John Lindahl
- John Potter
- Liam White
- Luke Meyer
- Michael Borish
- Patxi Fernandez-Zelaia
- Philip Bingham
- Priyanshi Agrawal
- Ritin Mathews
- Roger G Miller
- Sarah Graham
- Scott Smith
- Steven Guzorek
- Tomas Grejtak
- Venkatakrishnan Singanallur Vaidyanathan
- Vipin Kumar
- William Carter
- William Peter
- Yan-Ru Lin
- Ying Yang
- Yiyu Wang
- Yukinori Yamamoto

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

This manufacturing method uses multifunctional materials distributed volumetrically to generate a stiffness-based architecture, where continuous surfaces can be created from flat, rapidly produced geometries.

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.

A valve solution that prevents cross contamination while allowing for blocking multiple channels at once using only one actuator.

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

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.

In additive printing that utilizes multiple robotic agents to build, each agent, or “arm”, is currently limited to a prescribed path determined by the user.