DECP Funded Projects
Projects by Year
FY 2024 Distinguished Early Career Awards
DOE is awarding more than $3.1 million through its Distinguished Early Career Program to support four distinguished early career faculty in five states. This program invests in the innovative research and education programs of outstanding early career university faculty poised to pave new lines of inquiry and advance mission critical research directions in nuclear energy.
A complete list of the projects with their associated abstracts is available below.
| Title | Distinguished Faculty | Faculty Bio | Institution | Estimated Funding | Project Description | Abstract | |
|---|---|---|---|---|---|---|---|
| Establishing the Predictive Credibility of Data-Driven | Dr. Xu Wu | Biography | North Carolina State University | $625,000 | The objective is to establish and enhance the predictive credibility of data-driven Scientific Machine Learning (SciML) for nuclear applications through rigorous uncertainty quantification of SciML models to establish confidence, as well as deep generative learning to address the data scarcity issue. The project will augment the applications of SciML in nuclear energy (NE) scientific computing and prepare the students for transformative solutions across various DOE missions through six education and three leadership thrusts areas. | Document | FY2024 |
| Integrating Thermal Hydraulic Simulation and Experimentation with Data-Driven Methods to Support Molten Salt Reactors Development | Dr. Yang Liu | Biography | Texas A&M University | $625,000 | This proposal aims to develop a framework based on data-driven methods to integrate thermal hydraulics experimentation and simulation. The framework will result in a fast response multiscale data engine for efficient transient analysis for advanced nuclear reactors. The proposed framework will support molten salt reactor development through applications on heat exchanger optimization, transient analysis, and risk-informed analysis to demonstrate its applicability. | Document | FY2024 |
| Development of Computational Methods for Neutron Noise Analysis: Improving Modeling and Understanding of Perturbations in Light Water Reactors | Dr. Hunter Belanger | Biography | Rensselaer Polytechnic Institute | $625,000 | Vibrational perturbations in nuclear reactors lead to perturbations in the static neutron flux. In order to identify the location and type of vibration, special computational tools are neededÊ to simulate their effects on the flux. Such simulations are often done in the frequency domain, and the solution is therefore a complex quantity. This project aims to transformÊ understanding of these perturbations through advancing current Monte Carlo methods to simulate these phenomena. | Document | FY2024 |
| Lagrangian Particle Tracking Methods for Multiscale Graphite Dust Transport in Pebble Bed Reactors | Dr. April Novak | Biography | University of Illinois at Urbana-Champaign | $625,000 | Graphite dust poses a challenge to graphite-moderated reactors, acting as a mobile source term and impediment to heat transfer. This project will develop a new capability for Lagrangian particle tracking methods in MOOSE.Ê These numerical methods will be deployed to a multiscale full primary loop model of a pebble bed reactor using Pronghorn and SAM, in order to explore key questions regarding graphite dust transport physics, operations and maintenance strategies, and source term. | Document | FY2024 |
| The Application of Dynamic PRA to Revolutionize the PRA Model Development during the Design, Licensing, and Maintenance Activities of Current LWRs and Advanced Reactors | Dr. Mihai A. Diaconeasa | Biography | North Carolina State University | $625,000 | The main objective of the proposed work is to demonstrate the way dynamic PRA insights can be used to rethink how the completeness problem of the PRA models can be addressed during the design, licensing, and maintenance activities of current LWRs and advanced reactors by including dynamics observed during actual operating events. | Document | FY2023 |
| Advanced Surface Modification Strategies for Reliability Enhancement of Accident Tolerant Fuel Cladding in Nuclear Reactors | Dr. Sougata Roy | Biography | Iowa State University | $624,989 | Proposed project will explore the capability of the multi-feeder laser powder DED and in-situ mechanical working-based hybrid DED technology developed at UND for surface modification of accident tolerant fuel claddings used in light water nuclear reactors. Post-fabrication detailed microstructural characterization and property evaluation, in particular hardness, tensile behavior and wear resistance characteristics of test samples, will be explored. | Document | FY2023 |
| An Optimization and Control Hub for Advanced Reactors: A Step Toward Modernizing Nuclear Engineering Education | Dr. Majdi Radaideh | Biography | University of Michigan | $625,000 | This project aims to develop a foundational paradigm that provides innovative optimization and control solutions to support DOE-NE synergistic advanced reactor programs. The key aspect of this planned work is based on an established framework enhanced with these novel contributions: (1) diverse bio-inspired ensemble optimizer with surrogate modeling for reactor siting & core-reload optimization, (2) hybrid model predictive reinforcement learning controller for microreactors, and (3) modern integrated research and teaching plan. | Document | FY2023 |
| Using Machine Learning to Understand the Transient Critical Heat Flux and Post-CHF Heat Transfer | Dr. Juliana Pacheco Duarte | Biography | University of Wisconsin | $625,000 | To answer crucial questions on transient critical heat flux and post-CHF heat transfer behavior, the project plans to conduct experiments using high-resolution distributed temperature sensors in a directly heated fuel rod simulator at prototypical LWR accident conditions and use machine learning methods to improve the predictability capabilities of relevant computational codes. Two educational developments are proposed to promote broader and more inclusive nuclear engineering learning. | Document | FY2023 |
| Improving resistance of ferritic-martensitic steels to environmental degradation in advanced nuclear reactors | Xing Wang | Biography | Pennsylvania State University | $625,000 | This project aims to improve the resistance of ferritic-martensitic (FM) steels to environmental degradation in advanced reactors via two technical objectives: (i) design creep-tolerant FM steels with superior swelling resistance based on systematic understanding of the evolution of nanosized precipitates under extended irradiation and (ii) develop novel refractory high entropy alloy coatings to suppress the corrosion of FM steels in molten fluoride salts. | Document | FY2023 |
| Robot-assisted Online Monitoring, Online Maintenance, and Dynamic Risk Assessment for LWRs and Advanced Reactors | Dr. Fan Zhang | Biography | Georgia Institute of Technology | $625,000 | A robot-assisted online monitoring, online maintenance, and dynamic risk assessment platform for LWRs and advanced reactors will be developed. This project will integrate a 3D nuclear power plant (NPP) digital twin with data from a pressurized water reactor (PWR) simulator to enable robotic navigation and manipulation research, and will be used to develop algorithms for autonomous fault detection, diagnosis, and risk assessment integrating robot assistance. Research will be demonstrated both virtually and in a real laboratory environment. | Document | FY2022 |
| The application of advanced high resolution optical diagnostics to answer long standing questions and make new discoveries in boiling heat transfer in LWR conditions | Dr. Matteo Bucci | Biography | Massachusetts Institute of Technology | $625,000 | This project will study boiling heat transfer and the boiling crisis in prototypical light water reactor (LWR) conditions. High-resolution optical diagnostics will be utilized to measure the time-dependent temperature, heat flux, and vapor phase distribution on the boiling surface, the vapor distribution and velocity in the flow. These measurements will allow finding an answer to long-standing dilemma related to the boiling of water and the boiling crisis in nuclear reactor conditions. | Document | FY2022 |
| Physics-Informed Machine Learning to Accelerate Process Modeling in Additive Manufacturing of Structure Materials for Nuclear Industries | Dr. Amrita Basak | Biography | Pennsylvania State University | $625,000 | The goal of this research is directed toward developing scientific and formalized physics-informed data-driven techniques toward accelerating the generation of both forward and inverse scaling laws that can be transferred across material systems or manufacturing processes to understand the fundamental linkages between processing and the properties of interest in metal additive manufacturing (AM). | Document | FY2022 |
| Developing Digital Twins from High Fidelity Simulations | Dr. Brendan Kochunas | Biography | University of Michigan | $625,000 | The objective of this project is to develop the fundamental methods and techniques that would leverage advanced modeling and simulation to create efficient and accurate hybrid or integrated (e.g. physics based + data driven + machine learning) models. The project will have 5 majors tasks: developing hybrid models, investigating efficient learning strategies, V&V, incorporating UQ, and developing a new flexible curriculum to teach these methods. | Document | FY2022 |
| ARISE: Advanced Reactors Integral and Separate Effects Tests – An Integrated Research and Education Program | Dr. Minghui Chen | Biography | University of New Mexico | $625,000 | The objective of this integrated research and educational program is to perform separate effects tests (SETs) and integral effects tests (IETs) using a versatile molten salt test facility to validate system codes in support of the deployment of molten salt reactor (MSR) and Fluoride salt-cooled, High-temperature Reactors (FHRs) technologies and the expanded use of nuclear energy worldwide, and to offer students from undergraduate to graduate, especially Native American, Hispanic and underrepresented minorities, various training and education opportunities of advanced reactors and hands-on molten salt experiments. | Document | FY2022 |
FY 2023 Distinguished Early Career Awards
DOE is awarding more than $3.1 million through its Distinguished Early Career Program to support five distinguished early career faculty in five states. This program invests in the innovative research and education programs of outstanding early career university faculty poised to pave new lines of inquiry and advance mission critical research directions in nuclear energy.
A complete list of the projects with their associated abstracts is available below.
| Title | Distinguished Faculty | Faculty Bio | Institution | Estimated Funding | Project Description | Abstract | |
|---|---|---|---|---|---|---|---|
| Establishing the Predictive Credibility of Data-Driven | Dr. Xu Wu | Biography | North Carolina State University | $625,000 | The objective is to establish and enhance the predictive credibility of data-driven Scientific Machine Learning (SciML) for nuclear applications through rigorous uncertainty quantification of SciML models to establish confidence, as well as deep generative learning to address the data scarcity issue. The project will augment the applications of SciML in nuclear energy (NE) scientific computing and prepare the students for transformative solutions across various DOE missions through six education and three leadership thrusts areas. | Document | FY2024 |
| Integrating Thermal Hydraulic Simulation and Experimentation with Data-Driven Methods to Support Molten Salt Reactors Development | Dr. Yang Liu | Biography | Texas A&M University | $625,000 | This proposal aims to develop a framework based on data-driven methods to integrate thermal hydraulics experimentation and simulation. The framework will result in a fast response multiscale data engine for efficient transient analysis for advanced nuclear reactors. The proposed framework will support molten salt reactor development through applications on heat exchanger optimization, transient analysis, and risk-informed analysis to demonstrate its applicability. | Document | FY2024 |
| Development of Computational Methods for Neutron Noise Analysis: Improving Modeling and Understanding of Perturbations in Light Water Reactors | Dr. Hunter Belanger | Biography | Rensselaer Polytechnic Institute | $625,000 | Vibrational perturbations in nuclear reactors lead to perturbations in the static neutron flux. In order to identify the location and type of vibration, special computational tools are neededÊ to simulate their effects on the flux. Such simulations are often done in the frequency domain, and the solution is therefore a complex quantity. This project aims to transformÊ understanding of these perturbations through advancing current Monte Carlo methods to simulate these phenomena. | Document | FY2024 |
| Lagrangian Particle Tracking Methods for Multiscale Graphite Dust Transport in Pebble Bed Reactors | Dr. April Novak | Biography | University of Illinois at Urbana-Champaign | $625,000 | Graphite dust poses a challenge to graphite-moderated reactors, acting as a mobile source term and impediment to heat transfer. This project will develop a new capability for Lagrangian particle tracking methods in MOOSE.Ê These numerical methods will be deployed to a multiscale full primary loop model of a pebble bed reactor using Pronghorn and SAM, in order to explore key questions regarding graphite dust transport physics, operations and maintenance strategies, and source term. | Document | FY2024 |
| The Application of Dynamic PRA to Revolutionize the PRA Model Development during the Design, Licensing, and Maintenance Activities of Current LWRs and Advanced Reactors | Dr. Mihai A. Diaconeasa | Biography | North Carolina State University | $625,000 | The main objective of the proposed work is to demonstrate the way dynamic PRA insights can be used to rethink how the completeness problem of the PRA models can be addressed during the design, licensing, and maintenance activities of current LWRs and advanced reactors by including dynamics observed during actual operating events. | Document | FY2023 |
| Advanced Surface Modification Strategies for Reliability Enhancement of Accident Tolerant Fuel Cladding in Nuclear Reactors | Dr. Sougata Roy | Biography | Iowa State University | $624,989 | Proposed project will explore the capability of the multi-feeder laser powder DED and in-situ mechanical working-based hybrid DED technology developed at UND for surface modification of accident tolerant fuel claddings used in light water nuclear reactors. Post-fabrication detailed microstructural characterization and property evaluation, in particular hardness, tensile behavior and wear resistance characteristics of test samples, will be explored. | Document | FY2023 |
| An Optimization and Control Hub for Advanced Reactors: A Step Toward Modernizing Nuclear Engineering Education | Dr. Majdi Radaideh | Biography | University of Michigan | $625,000 | This project aims to develop a foundational paradigm that provides innovative optimization and control solutions to support DOE-NE synergistic advanced reactor programs. The key aspect of this planned work is based on an established framework enhanced with these novel contributions: (1) diverse bio-inspired ensemble optimizer with surrogate modeling for reactor siting & core-reload optimization, (2) hybrid model predictive reinforcement learning controller for microreactors, and (3) modern integrated research and teaching plan. | Document | FY2023 |
| Using Machine Learning to Understand the Transient Critical Heat Flux and Post-CHF Heat Transfer | Dr. Juliana Pacheco Duarte | Biography | University of Wisconsin | $625,000 | To answer crucial questions on transient critical heat flux and post-CHF heat transfer behavior, the project plans to conduct experiments using high-resolution distributed temperature sensors in a directly heated fuel rod simulator at prototypical LWR accident conditions and use machine learning methods to improve the predictability capabilities of relevant computational codes. Two educational developments are proposed to promote broader and more inclusive nuclear engineering learning. | Document | FY2023 |
| Improving resistance of ferritic-martensitic steels to environmental degradation in advanced nuclear reactors | Xing Wang | Biography | Pennsylvania State University | $625,000 | This project aims to improve the resistance of ferritic-martensitic (FM) steels to environmental degradation in advanced reactors via two technical objectives: (i) design creep-tolerant FM steels with superior swelling resistance based on systematic understanding of the evolution of nanosized precipitates under extended irradiation and (ii) develop novel refractory high entropy alloy coatings to suppress the corrosion of FM steels in molten fluoride salts. | Document | FY2023 |
| Robot-assisted Online Monitoring, Online Maintenance, and Dynamic Risk Assessment for LWRs and Advanced Reactors | Dr. Fan Zhang | Biography | Georgia Institute of Technology | $625,000 | A robot-assisted online monitoring, online maintenance, and dynamic risk assessment platform for LWRs and advanced reactors will be developed. This project will integrate a 3D nuclear power plant (NPP) digital twin with data from a pressurized water reactor (PWR) simulator to enable robotic navigation and manipulation research, and will be used to develop algorithms for autonomous fault detection, diagnosis, and risk assessment integrating robot assistance. Research will be demonstrated both virtually and in a real laboratory environment. | Document | FY2022 |
| The application of advanced high resolution optical diagnostics to answer long standing questions and make new discoveries in boiling heat transfer in LWR conditions | Dr. Matteo Bucci | Biography | Massachusetts Institute of Technology | $625,000 | This project will study boiling heat transfer and the boiling crisis in prototypical light water reactor (LWR) conditions. High-resolution optical diagnostics will be utilized to measure the time-dependent temperature, heat flux, and vapor phase distribution on the boiling surface, the vapor distribution and velocity in the flow. These measurements will allow finding an answer to long-standing dilemma related to the boiling of water and the boiling crisis in nuclear reactor conditions. | Document | FY2022 |
| Physics-Informed Machine Learning to Accelerate Process Modeling in Additive Manufacturing of Structure Materials for Nuclear Industries | Dr. Amrita Basak | Biography | Pennsylvania State University | $625,000 | The goal of this research is directed toward developing scientific and formalized physics-informed data-driven techniques toward accelerating the generation of both forward and inverse scaling laws that can be transferred across material systems or manufacturing processes to understand the fundamental linkages between processing and the properties of interest in metal additive manufacturing (AM). | Document | FY2022 |
| Developing Digital Twins from High Fidelity Simulations | Dr. Brendan Kochunas | Biography | University of Michigan | $625,000 | The objective of this project is to develop the fundamental methods and techniques that would leverage advanced modeling and simulation to create efficient and accurate hybrid or integrated (e.g. physics based + data driven + machine learning) models. The project will have 5 majors tasks: developing hybrid models, investigating efficient learning strategies, V&V, incorporating UQ, and developing a new flexible curriculum to teach these methods. | Document | FY2022 |
| ARISE: Advanced Reactors Integral and Separate Effects Tests – An Integrated Research and Education Program | Dr. Minghui Chen | Biography | University of New Mexico | $625,000 | The objective of this integrated research and educational program is to perform separate effects tests (SETs) and integral effects tests (IETs) using a versatile molten salt test facility to validate system codes in support of the deployment of molten salt reactor (MSR) and Fluoride salt-cooled, High-temperature Reactors (FHRs) technologies and the expanded use of nuclear energy worldwide, and to offer students from undergraduate to graduate, especially Native American, Hispanic and underrepresented minorities, various training and education opportunities of advanced reactors and hands-on molten salt experiments. | Document | FY2022 |
FY 2022 Distinguished Early Career Awards
DOE is awarding more than $3.1 million through its newly established Distinguished Early Career Program to support five early career faculty in five states.
A complete list of the projects with their associated abstracts is available below.
| Title | Distinguished Faculty | Faculty Bio | Institution | Estimated Funding | Project Description | Abstract | |
|---|---|---|---|---|---|---|---|
| Establishing the Predictive Credibility of Data-Driven | Dr. Xu Wu | Biography | North Carolina State University | $625,000 | The objective is to establish and enhance the predictive credibility of data-driven Scientific Machine Learning (SciML) for nuclear applications through rigorous uncertainty quantification of SciML models to establish confidence, as well as deep generative learning to address the data scarcity issue. The project will augment the applications of SciML in nuclear energy (NE) scientific computing and prepare the students for transformative solutions across various DOE missions through six education and three leadership thrusts areas. | Document | FY2024 |
| Integrating Thermal Hydraulic Simulation and Experimentation with Data-Driven Methods to Support Molten Salt Reactors Development | Dr. Yang Liu | Biography | Texas A&M University | $625,000 | This proposal aims to develop a framework based on data-driven methods to integrate thermal hydraulics experimentation and simulation. The framework will result in a fast response multiscale data engine for efficient transient analysis for advanced nuclear reactors. The proposed framework will support molten salt reactor development through applications on heat exchanger optimization, transient analysis, and risk-informed analysis to demonstrate its applicability. | Document | FY2024 |
| Development of Computational Methods for Neutron Noise Analysis: Improving Modeling and Understanding of Perturbations in Light Water Reactors | Dr. Hunter Belanger | Biography | Rensselaer Polytechnic Institute | $625,000 | Vibrational perturbations in nuclear reactors lead to perturbations in the static neutron flux. In order to identify the location and type of vibration, special computational tools are neededÊ to simulate their effects on the flux. Such simulations are often done in the frequency domain, and the solution is therefore a complex quantity. This project aims to transformÊ understanding of these perturbations through advancing current Monte Carlo methods to simulate these phenomena. | Document | FY2024 |
| Lagrangian Particle Tracking Methods for Multiscale Graphite Dust Transport in Pebble Bed Reactors | Dr. April Novak | Biography | University of Illinois at Urbana-Champaign | $625,000 | Graphite dust poses a challenge to graphite-moderated reactors, acting as a mobile source term and impediment to heat transfer. This project will develop a new capability for Lagrangian particle tracking methods in MOOSE.Ê These numerical methods will be deployed to a multiscale full primary loop model of a pebble bed reactor using Pronghorn and SAM, in order to explore key questions regarding graphite dust transport physics, operations and maintenance strategies, and source term. | Document | FY2024 |
| The Application of Dynamic PRA to Revolutionize the PRA Model Development during the Design, Licensing, and Maintenance Activities of Current LWRs and Advanced Reactors | Dr. Mihai A. Diaconeasa | Biography | North Carolina State University | $625,000 | The main objective of the proposed work is to demonstrate the way dynamic PRA insights can be used to rethink how the completeness problem of the PRA models can be addressed during the design, licensing, and maintenance activities of current LWRs and advanced reactors by including dynamics observed during actual operating events. | Document | FY2023 |
| Advanced Surface Modification Strategies for Reliability Enhancement of Accident Tolerant Fuel Cladding in Nuclear Reactors | Dr. Sougata Roy | Biography | Iowa State University | $624,989 | Proposed project will explore the capability of the multi-feeder laser powder DED and in-situ mechanical working-based hybrid DED technology developed at UND for surface modification of accident tolerant fuel claddings used in light water nuclear reactors. Post-fabrication detailed microstructural characterization and property evaluation, in particular hardness, tensile behavior and wear resistance characteristics of test samples, will be explored. | Document | FY2023 |
| An Optimization and Control Hub for Advanced Reactors: A Step Toward Modernizing Nuclear Engineering Education | Dr. Majdi Radaideh | Biography | University of Michigan | $625,000 | This project aims to develop a foundational paradigm that provides innovative optimization and control solutions to support DOE-NE synergistic advanced reactor programs. The key aspect of this planned work is based on an established framework enhanced with these novel contributions: (1) diverse bio-inspired ensemble optimizer with surrogate modeling for reactor siting & core-reload optimization, (2) hybrid model predictive reinforcement learning controller for microreactors, and (3) modern integrated research and teaching plan. | Document | FY2023 |
| Using Machine Learning to Understand the Transient Critical Heat Flux and Post-CHF Heat Transfer | Dr. Juliana Pacheco Duarte | Biography | University of Wisconsin | $625,000 | To answer crucial questions on transient critical heat flux and post-CHF heat transfer behavior, the project plans to conduct experiments using high-resolution distributed temperature sensors in a directly heated fuel rod simulator at prototypical LWR accident conditions and use machine learning methods to improve the predictability capabilities of relevant computational codes. Two educational developments are proposed to promote broader and more inclusive nuclear engineering learning. | Document | FY2023 |
| Improving resistance of ferritic-martensitic steels to environmental degradation in advanced nuclear reactors | Xing Wang | Biography | Pennsylvania State University | $625,000 | This project aims to improve the resistance of ferritic-martensitic (FM) steels to environmental degradation in advanced reactors via two technical objectives: (i) design creep-tolerant FM steels with superior swelling resistance based on systematic understanding of the evolution of nanosized precipitates under extended irradiation and (ii) develop novel refractory high entropy alloy coatings to suppress the corrosion of FM steels in molten fluoride salts. | Document | FY2023 |
| Robot-assisted Online Monitoring, Online Maintenance, and Dynamic Risk Assessment for LWRs and Advanced Reactors | Dr. Fan Zhang | Biography | Georgia Institute of Technology | $625,000 | A robot-assisted online monitoring, online maintenance, and dynamic risk assessment platform for LWRs and advanced reactors will be developed. This project will integrate a 3D nuclear power plant (NPP) digital twin with data from a pressurized water reactor (PWR) simulator to enable robotic navigation and manipulation research, and will be used to develop algorithms for autonomous fault detection, diagnosis, and risk assessment integrating robot assistance. Research will be demonstrated both virtually and in a real laboratory environment. | Document | FY2022 |
| The application of advanced high resolution optical diagnostics to answer long standing questions and make new discoveries in boiling heat transfer in LWR conditions | Dr. Matteo Bucci | Biography | Massachusetts Institute of Technology | $625,000 | This project will study boiling heat transfer and the boiling crisis in prototypical light water reactor (LWR) conditions. High-resolution optical diagnostics will be utilized to measure the time-dependent temperature, heat flux, and vapor phase distribution on the boiling surface, the vapor distribution and velocity in the flow. These measurements will allow finding an answer to long-standing dilemma related to the boiling of water and the boiling crisis in nuclear reactor conditions. | Document | FY2022 |
| Physics-Informed Machine Learning to Accelerate Process Modeling in Additive Manufacturing of Structure Materials for Nuclear Industries | Dr. Amrita Basak | Biography | Pennsylvania State University | $625,000 | The goal of this research is directed toward developing scientific and formalized physics-informed data-driven techniques toward accelerating the generation of both forward and inverse scaling laws that can be transferred across material systems or manufacturing processes to understand the fundamental linkages between processing and the properties of interest in metal additive manufacturing (AM). | Document | FY2022 |
| Developing Digital Twins from High Fidelity Simulations | Dr. Brendan Kochunas | Biography | University of Michigan | $625,000 | The objective of this project is to develop the fundamental methods and techniques that would leverage advanced modeling and simulation to create efficient and accurate hybrid or integrated (e.g. physics based + data driven + machine learning) models. The project will have 5 majors tasks: developing hybrid models, investigating efficient learning strategies, V&V, incorporating UQ, and developing a new flexible curriculum to teach these methods. | Document | FY2022 |
| ARISE: Advanced Reactors Integral and Separate Effects Tests – An Integrated Research and Education Program | Dr. Minghui Chen | Biography | University of New Mexico | $625,000 | The objective of this integrated research and educational program is to perform separate effects tests (SETs) and integral effects tests (IETs) using a versatile molten salt test facility to validate system codes in support of the deployment of molten salt reactor (MSR) and Fluoride salt-cooled, High-temperature Reactors (FHRs) technologies and the expanded use of nuclear energy worldwide, and to offer students from undergraduate to graduate, especially Native American, Hispanic and underrepresented minorities, various training and education opportunities of advanced reactors and hands-on molten salt experiments. | Document | FY2022 |
*Actual project funding will be established during the award negotiation phase.
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