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Researcher
- Chris Tyler
- Justin West
- Ritin Mathews
- Edgar Lara-Curzio
- Ying Yang
- Yong Chae Lim
- Zhili Feng
- Adam Willoughby
- Brian Post
- Bruce A Pint
- David Olvera Trejo
- Eric Wolfe
- J.R. R Matheson
- Jaydeep Karandikar
- Jian Chen
- Rangasayee Kannan
- Rishi Pillai
- Ryan Dehoff
- Scott Smith
- Steven J Zinkle
- Wei Zhang
- Yanli Wang
- Yutai Kato
- Adam Stevens
- Akash Jag Prasad
- Alice Perrin
- Ben Lamm
- Beth L Armstrong
- Bishnu Prasad Thapaliya
- Brandon Johnston
- Brian Gibson
- Bryan Lim
- Calen Kimmell
- Charles Hawkins
- Christopher Ledford
- Dali Wang
- Emma Betters
- Frederic Vautard
- Greg Corson
- Jesse Heineman
- Jiheon Jun
- John Potter
- Josh B Harbin
- Marie Romedenne
- Meghan Lamm
- Michael Kirka
- Nidia Gallego
- Patxi Fernandez-Zelaia
- Peeyush Nandwana
- Priyanshi Agrawal
- Roger G Miller
- Sarah Graham
- Shajjad Chowdhury
- Sudarsanam Babu
- Tim Graening Seibert
- Tolga Aytug
- Tomas Grejtak
- Tony L Schmitz
- 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.

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).

A novel method that prevents detachment of an optical fiber from a metal/alloy tube and allows strain measurement up to higher temperatures, about 800 C has been developed. Standard commercial adhesives typically only survive up to about 400 C.

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.

The microreactor design addresses the need to understand molten salt-assisted electrochemical processes at a controlled scale, enabling real-time observation of structural changes and kinetics.

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.

With the ever-growing reliance on batteries, the need for the chemicals and materials to produce these batteries is also growing accordingly. One area of critical concern is the need for high quality graphite to ensure adequate energy storage capacity and battery stability.