The annual collaboration fund is designed to provide funding to selected proposals by Idaho National Laboratory researchers that would enhance collaborative relationships with CAES universities, in line with the CAES strategic plan. The goal is to establish and foster relationships between the CAES entities in research, education and innovation. Applications for FY22 are being accepted until March 18. Go here for more information or to apply.
Here are the recipients from 2021:
Collaborators | Project title | CAES focus area(s) |
INL's Joshua Hansel, Nuclear Science and Technology (NS&T) Directorate and Amir Ali, Idaho State University | Nuclear Microreactor Heat Pipe Modeling and Simulation Database | Nuclear Energy/ Computing, Data, and Visualization |
INL's Kunal Mondal, Energy and Environment Science and Technology (EES&T)) Directorate, and Mustafa Mashal, Bruce Savage, Rene Rodriguez, and Kavita Sharma, Idaho State University
|
Bulk Storage of Hydrogen Energy | Advanced Manufacturing |
Lu Cai, INL (EES&T), and Lan Li, Boise State University | Thermal Analysis of Nuclear Materials | Nuclear Energy |
INL's Bryon Marsh, National and Homeland Security (N&HS) Directorate, and Mustafa Mashal, Idaho State University | Radiological Dispersal Device Training | Nuclear Energy
|
INL's Craig Rieger, (N&HS), and Costas Kolias, University of Idaho | Evaluation of USB Peripherals | Cybersecurity |
INL's Boopathy Kombaiah, Materials and Fuels Complex (MFC), and Indrajit Charit, University of Idaho | Manufacturing Materials Development | Advanced Manufacturing/ Nuclear Energy |
INL's Amy Lientz, (EES&T, NS&T, and N&HS), and Karen Corral and Jim Kroes, Boise State University | Growing the Next Generation of Supply Chain Professionals | Cybersecurity |
INL's SM Shafiul Alam, (EES&T), and Yacine Chakhcoukh, University of Idaho | Cyber Vulnerability Issues of Distribution Systems | Cybersecurity/ Innovative Energy Systems |
INL's Som Dhulipala, (NS&T), and Leslie Kerby, Idaho State University, and Lars Kotthoff, University of Wyoming | Randomized Computing for Multiphysics Modeling and Simulations | Computing, Data, and Visualization
|
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