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Researcher
- Chris Tyler
- Justin West
- Ritin Mathews
- Hongbin Sun
- Srikanth Yoginath
- Chad Steed
- David Olvera Trejo
- J.R. R Matheson
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- Pablo Moriano Salazar
- Peeyush Nandwana
- Pradeep Ramuhalli
- Praveen Cheekatamarla
- Rangasayee Kannan
- Ruhul Amin
- Samudra Dasgupta
- Thien D. Nguyen
- Todd Thomas
- Tomas Grejtak
- Tony L Schmitz
- Varisara Tansakul
- Vishaldeep Sharma
- Vittorio Badalassi
- Vladimir Orlyanchik
- Xiuling Nie
- Yiyu Wang

In nuclear and industrial facilities, fine particles, including radioactive residues—can accumulate on the interior surfaces of ventilation ducts and equipment, posing serious safety and operational risks.

Often there are major challenges in developing diverse and complex human mobility metrics systematically and quickly.

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.

The invention presented here addresses key challenges associated with counterfeit refrigerants by ensuring safety, maintaining system performance, supporting environmental compliance, and mitigating health and legal risks.

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.

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.

A novel approach is presented herein to improve time to onset of natural convection stemming from fuel element porosity during a failure mode of a nuclear reactor.

Digital twins (DTs) have emerged as essential tools for monitoring, predicting, and optimizing physical systems by using real-time data.

Simulation cloning is a technique in which dynamically cloned simulations’ state spaces differ from their parent simulation due to intervening events.