CINR Phase II Continuation Funded Projects
Projects by Year
FY 2024 CINR Phase II Continuation Awards
Six university-led projects will receive more than $4.7 million for research that complement and enhance ongoing NEUP research.
A full list of CINR Phase II Continuation recipients is listed below.
| Title | Institution | Estimated Funding* | Project Description | Abstract | Project Type | |
|---|---|---|---|---|---|---|
| Center for Thermal-Fluids Applications in Nuclear Energy: Toward Industry Adoption | Pennsylvania State University | $1,458,693.00 | Building on a remarkably successful Phase I, Phase II Continuation of the Center for Thermal-Fluids Applications in Nuclear Energy aims to enhance transient modeling for advanced reactors by researching novel scale-bridging methodologies. The team will leverage new high-resolution data, made possible by Graphics Processing Unit (GPU) computing, to develop efficient thermal hydraulics systems analysis methods. The team will also integrate Large Language Models to streamline the multiscale framework and foster industry adoption. | Document | Integrated Research Projects | FY2024 |
| Multi-physics fuel performance modeling of TRISO-bearing fuel in advanced reactor environments | University of Tennessee at Knoxville | $1,250,000.00 | The focus of this project is to develop and validate coupled multi-physics TRi-structural ISOtropic (TRISO) fuel performance models for high temperature gas cooled reactors, including both pebble bed modular high temperature gas cooled reactors and microreactors, as well as prismatic microreactors similar to eVinci. This builds upon the recent NEUP IRP project (20-22094) that was focused on pebble bed fluoride salt cooled high temperature reactors Fluoride Salt-Cooled High-Temperature Reactor (FHR) and historical prismatic Modular High-Temperature Gas-Cooled Reactor (mHTGR) designs. | Document | Integrated Research Projects | FY2024 |
| Enhancing Multimodal Tomography for Nuclear Applications using Machine Learning | Colorado School of Mines | $533,333.00 | The team will develop methods based on machine learning for upsampling and denoising muon, gamma and neutron tomographic images of spent nuclear fuel casks. The team will develop methods based on machine learning to improve both the resolution and signal-to-noise ratios of passive multimodal tomography images. This work will dramatically enhance the sensitivity of dry cask imaging technologies that are essential for the long-term sustainability of nuclear power in the United States. | Document | Research and Development | FY2024 |
| Prediction, scale-up, and optimization of used nuclear fuel processes using hydroxypyridinone-based hold-back reagents for actinide and fission product recovery | University of California, Berkeley | $400,000.00 | The teams studies have shown the applicability of hydroxypyridinone ligand architectures to drive the efficient separation of target elements and operate under the extreme conditions of a multi-component radiation field. This project seeks to optimize and scale-up this new approach, combined with multi-scale modeling for the prediction of radiolytic ligand longevity and degradation product formation over time, so as to augment at-scale engineering models in support of future process implementation. | Document | Research and Development | FY2024 |
| Developing constitutive relationships for the properties of unsaturated bentonite buffers under high temperatures | University of California, San Diego | $533,333.00 | Phase II continuation of this project is focused on simulating the effects of high temperatures (up to 200 ¡C) on the coupled heat transfer, water flow, and volume change in unsaturated, compacted granular bentonite using new material properties from Phase I of this project, as well as understanding and simulating the multiphase hydration process of bentonite buffers in deep geological repositories with closely spaced waste packages or Dual Purpose Containers such as that evaluated in the High Temperature Effects on Bentonite Buffers (HotBENT) project. | Document | Research and Development | FY2024 |
| Correlating buffer microstructure with failure progression into the SiC layer in TRISO | University of Wisconsin-Madison | $533,333.00 | Combining modeling and experiments, this Phase-II continuation will harness and extend the success of CINR 20-19556 to establish an Irradiation-Microstructure-Property-Performance (IMPP) correlation that links initial buffer microstructure with fracture initiation and progression to the Silicon carbide (SiC) layer in TRi-structural ISOtropic (TRISO) particles. This correlation can be turned into design principles to further improve the irradiation performance of TRISO by controlling initial buffer microstructure. | Document | Research and Development | FY2024 |
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