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Researcher
- Brian Post
- Chris Tyler
- Peter Wang
- Justin West
- Rafal Wojda
- Ritin Mathews
- Andrzej Nycz
- Blane Fillingim
- Chris Masuo
- Peeyush Nandwana
- Prasad Kandula
- Ryan Dehoff
- Singanallur Venkatakrishnan
- Sudarsanam Babu
- Thomas Feldhausen
- Adam Stevens
- Ahmed Hassen
- Amir K Ziabari
- Christopher Fancher
- David Olvera Trejo
- Diana E Hun
- J.R. R Matheson
- Jaydeep Karandikar
- Joshua Vaughan
- Lauren Heinrich
- Michael Kirka
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- Rangasayee Kannan
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- Vandana Rallabandi
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- Akash Jag Prasad
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- Amy Elliott
- Beth L Armstrong
- Brian Gibson
- Bryan Maldonado Puente
- Calen Kimmell
- Cameron Adkins
- Christopher Ledford
- Corey Cooke
- Corson Cramer
- Craig Blue
- Emma Betters
- Fred List III
- Gina Accawi
- Gordon Robertson
- Greg Corson
- Gurneesh Jatana
- Isha Bhandari
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- Trevor Aguirre
- Vladimir Orlyanchik
- Vlastimil Kunc
- William Peter
- Yukinori Yamamoto

ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.

Misalignment issues of the PWPT system have been addressed. The intercell power transformer has been introduced in order to improve load sharing of the system during a mismatch of the primary single-phase coil and the secondary multi-phase coils.

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.

A pressure burst feature has been designed and demonstrated for relieving potentially hazardous excess pressure within irradiation capsules used in the ORNL High Flux Isotope Reactor (HFIR).

We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.

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.

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.

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.