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Researcher
- Yong Chae Lim
- Rangasayee Kannan
- Zhili Feng
- Adam Siekmann
- Adam Stevens
- Brian Post
- Bryan Lim
- Hongbin Sun
- Hong Wang
- Hyeonsup Lim
- Jian Chen
- Jiheon Jun
- Nate See
- Peeyush Nandwana
- Prashant Jain
- Priyanshi Agrawal
- Roger G Miller
- Ryan Dehoff
- Sarah Graham
- Sudarsanam Babu
- Thien D. Nguyen
- Tomas Grejtak
- Vivek Sujan
- Wei Zhang
- William Peter
- Yiyu Wang
- Yukinori Yamamoto

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.

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

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 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.

No readily available public data exists for vehicle class and weight information that covers the entire U.S. highway network. The Travel Monitoring Analysis System, managed by the Federal Highway Administration covers only less than 1% of the US highway network.

The technologies provide a coating method to produce corrosion resistant and electrically conductive coating layer on metallic bipolar plates for hydrogen fuel cell and hydrogen electrolyzer applications.

Welding high temperature and/or high strength materials for aerospace or automobile manufacturing is challenging.

Pairing hybrid neural network modeling techniques with artificial intelligence, or AI, controls has resulted in a unique hybrid system that creates a smart solution for traffic-signal timing.