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DOE OSTI2023

Data-Driven Model Predictive Control for Temperature Management of Heat Pipe Microreactor

A data-driven model predictive control (MPC) was developed to enable the self-regulating capability of heat pipe (HP) nuclear microreactors. The MPC can proactively respond to potential disturbances of HP microreactors using three approaches for system identifications: linear state-space model, feedforward neural network, and recurrent neural networks with long short-term memory units. We present numerical results of data-driven MPCs to control the temperatures of selected HPs in a 37-HP test article. Our results show qualitatively that all data-driven MPCs produced similar control actions, while quantitatively, with artificial neural nets (especially feedforward neural nets), MPC can better follow drastic changes in setpoints with small errors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Regulatory Research Planning for Micro-Reactor Development

A limited-scope Regulatory Research Development Plan (RRDP) is being developed to link important advanced non light water nuclear microreactor technology research and development (R&D) activities sponsored by the U.S. Department of Energy’s Office of Nuclear Energy (DOE NE), Science, and Technology to regulatory requirements and critical licensing needs likely to impact the deployment of a domestic commercial microreactor fleet. This document is a precursor to that forthcoming limited scope microreactor RRDP. This report is being published to aid in the identification of key fiscal year (FY) 2022 topical research opportunities (as conveyed to the RRDP development team) by respondent microreactor developers and suppliers in consideration of micro-reactor regulatory needs and challenges noted by industry, DOE, and Nuclear Regulatory Commission (NRC) stakeholders. Although this document does not contain the regulatory effects analysis and R&D recommendations that is expected in the final RRDP, this document is being released now to assist DOE researchers and investigators in FY22 research planning activities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Evaluation of the MARVEL Reactor Inhalation Dose Consequences

A dose consequence analysis was performed to support the preliminary Microreactor Applications Research Validation and Evaluation Project (MARVEL) design effort. The purpose of the MARVEL project is to develop a nuclear microreactor applications test bed at Idaho National Laboratory (INL) to perform research and development on various operational features of microreactors to ultimately improve integration of microreactors to end-user applications. The MARVEL concept is a 100 kilowatt (kW) thermal (kWth) and approximately 20-kW electric (kWe) generating microreactor. The MARVEL system will be located in the INL TREAT facility in the north high-bay equipment pit. The analysis considers the bounding release fractions of the MARVEL reactor concept and documents the dose consequences to the public and collocated worker.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

A compact furnace to support in situ neutron imaging of hydrogen dynamics in yttrium hydride moderators

A compact, nuclear microreactor that utilizes low-enriched uranium fuel is a promising solution to meet U.S. energy demands in nonconventional nuclear markets such as remote and decentralized energy grids. Yttrium hydride (YHx) is a potential moderator material for a microreactor design that reduces the amount of required fuel and provides superior retention of hydrogen at high reactor operating temperatures. Hydrogen diffusion properties in YHx are highly sought after for computer model validation and reactor prototyping. To characterize hydrogen diffusion, a compact dual-zone furnace was developed at Los Alamos National Laboratory and analyzed via neutron imaging at the Los Alamos Neutron Science Center (LANSCE). The goal of these measurements is to assess hydrogen diffusion in YHx samples as a function of applied temperature gradients. Included herein is recent progress in technique and furnace developments as well as initial results from concentration- and temperature-gradient measurements at LANSCE.

Torres, James↗
DOE OSTI2024

ACCELERATING MICROREACTOR DEVELOPMENT AND DEPLOYMENT THROUGH JOINT PUBLIC TEST BEDS AND PRIVATE ADVANCED REACTOR DEVELOPMENT

The United States Department of Energy (DOE) has funded the National Reactor Innovation Center (NRIC) to accelerate the development and commercialization of small modular reactors and other advanced reactor technologies. As part of this effort NIRC is building two strategic assets at the Idaho National Laboratory (INL) to facilitate public-private partnerships for the development and testing of advanced nuclear microreactors and Small Modular Reactors (SMR). One will provide a safe, secure, and affordable location for High-Assay Low Enriched Uranium (HALEU) fueled reactors and a second for Highly Enriched Uranium (HEU) fueled reactors. Together these testbeds fill a nuclear testing infrastructure gap. The availability of such comprehensive testing facilities at the national labs eliminates the significant financial and operational burdens associated with each developer building and licensing their own test facilities. Consequently, this approach will not only accelerate technological innovation and reduce time-to-market for advanced nuclear solutions but it also underscores the DOE's commitment to fostering an ecosystem where nuclear energy will thrive as a clean, reliable, and efficient source of power. The Demonstration of Microreactor Experiments (DOME) and Laboratory for Operations and Testing in the United States (LOTUS) have planned availability in 2026, and 2027 respectively.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Additive Manufacturing of Heat Pipes for Microreactor Applications

Heat pipes are highly effective devices used to passively transport heat by two-phase capillary action. Their small footprint, light weight and lack of moving parts make them ideal for transportable nuclear microreactors, where size and weight are limited, minimal to no operation and maintenance are required, and high reliability is desired. The use of additive manufacturing allows for the fabrication of heat pipes with performance enhancements, such as microchannels, grooves, arteries, or tailored porosity, which are difficult, expensive or impossible to achieve with traditional fabrication techniques. We are evaluating the capabilities of the Admaflex 130 Digital Light Printer to produce these geometries by characterizing feature shrinkage, developing an optimal heat treatment recipe, assessing the effects of heat treatment atmosphere and varying print orientation. Computational simulations are being used to estimate performance of the various 3D printed configurations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

ECAR-5127 Rev 1 Evaluation of the MARVEL Reactor Inhalation Dose Consequences

The following dose consequence analysis is performed to support the preliminary Microreactor Applications Research Validation and Evaluation Project (MARVEL) design effort. The purpose of the MARVEL project is to develop a nuclear microreactor applications test bed at Idaho National Laboratory (INL) to perform research and development on various operational features of microreactors to ultimately improve integration of microreactors to end-user applications. The MARVEL concept is a 100 kilowatt (kW) thermal (kWth) and approximately 20-kW electric (kWe) generating microreactor. The MARVEL system will be located in the INL TREAT facility in the north high-bay equipment pit. This ECAR considers the bounding release fractions of the MARVEL reactor concept and documents the dose consequences to the public and collocated worker.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2024

Acoustic-based monitoring and machine learning of component status for microreactor applications

This report provides a description and assessment of recent efforts to couple acoustic-based experimental measurements and characterization with machine learning models in order to enhance structural health monitoring capabilities for nuclear microreactors. With resilient embedded sensors in development by others supported by programs funded by the US Department of Energy’s Office of Nuclear Energy, the work described herein builds upon ongoing efforts to improve non-destructive testing technology that relates measured acoustic signatures to component stresses and/or structural defects, using a combination of new experimental measurements and machine learning architectures. The experimental procedure remained similar to that developed for the previous year’s demonstration of damage detection by the authors, with the same damaged sample tested under similar applied stress conditions. Notably, a new mounting fixture was designed and implemented to improve measurement consistency and a more sophisticated laser Doppler vibrometer was employed to make high-fidelity vibration measurements. Two nominally identical sets of training data were collected for each experimental setup to better understand the repeatability of the experiment and to better test the generality of trained neural network models. Additionally, we obtained new high-quality 3D mode shapes of the damaged test article at various stress and excitation levels, providing greater insights into the physical response of the sample during testing. Previously, we demonstrated that a machine learning model based on a convolutional neural network can predict structural details of an artificially introduced interface (intact, rough cut, smooth cut), and the applied torque level. In this study, we have transitioned to graph-based neural network architectures to better develop and test a flexible framework that is more suitable to being transferred away from controlled benchtop experiments and into more applied settings where less-structured data inputs may be expected. In general, performance testing of a graph neural network on frequency-domain representations of the data indicates strong and consistent identification of test conditions for datasets recorded on damaged components. With goals of predicting damage location and other changing experimental conditions using limited datasets, predictive models using a graph neural network architecture correctly predicted the applied torque level with an accuracy of 85% using only a single measurement point and predicted within one torque level in 95% of test windows. Predictions of damage location had limited success due to the symmetry and minimal number of the damage scenarios presented during model training. Results were ambiguous as to whether the model could detect the location of the artificial damage, or if it was instead learning the location of a given measurement point on the part and subsequently detecting which points were closest to the location of the damage. This finding will be factored into upcoming planned work on damaged graphite components, where new experimental tests with a larger number and variety of damage scenarios are expected to provide improved validation of recent developments in monitoring methodology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

A two-phase three-field modeling framework for heat pipe application in nuclear reactors

Heat pipes and two-phase thermosyphons are highly efficient heat transfer devices utilizing continuous evaporation and condensation of working fluid for two-phase heat transport in closed systems. Because of the nearly isothermal and fully passive phase-change heat transfer mechanism, heat pipes and thermosyphons have found many applications in nuclear engineering, space technologies, and other energy systems. High-temperature heat pipes are used in nuclear microreactors to remove fission power from the primary system and are coupled with power conversion systems or process heat applications. Modeling of the two-phase flow phenomena inside a heat pipe is essential to its design and safety analysis. In this study, a comprehensive one-dimensional two-phase three-field flow model has been developed for the analysis of heat pipes in normal operation conditions and transients. The conservation or field equations of mass, momentum, and energy were developed for the liquid film, vapor, and droplet. In addition, constitutive models or correlations were reviewed thoroughly and provided for the closure of the three-field equations. Specific constitutive equations regarding interfacial mass and heat transfer at two interfaces, namely film-gas interface and gas-droplet interface, were reviewed for droplet entrainment and deposition rates as well as film and droplet evaporation rates. Furthermore, mechanistic correlations of annular flow film thickness were recommended for the modeling of the thermosyphons without a wick as a critical constitutive correlation. Furthermore, experimental data needs from new experiments using a prototype working fluid or surrogate fluids for the model validation of high-temperature heat pipes in microreactors were recommended for future research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Design and Optimization of a Gas-Cooled, Airfoil Fin Microchannel Heat Exchanger

High-performance microchannel heat exchangers are needed to supply heat for power conversion for nuclear microreactors. An airfoil fin microchannel design, constructed of Alloy 617 with helium as the working fluid, was analyzed and optimized using a design of experiments with artificial intelligence and machine learning techniques. The use of airfoil fins offers the potential to reduce pressure drop across the heat exchanger, as compared to other types of channel configurations. A framework for topology optimization of airfoil fin PCHEs has been developed that can be readily extended to different fin sizes and shapes, as well as different inlet and operating conditions, materials of construction, and working fluids. An optimization procedure was developed that employs computational fluid dynamics for a set of design points identified using Latin hypercube sampling. STAR-CCM+ was used to analyze a simplified two-channel configuration where five parameters were varied – inlet angle, fin scale, extent of staggering, transverse and longitudinal pitches. Two methods were compared for generating surrogate models – a 5D polynomial and a regression neural network. A response surface approximation was created from the surrogate models and input to a genetic algorithm. The genetic algorithm identified a set of optimal points on the Pareto front. The optimal geometry was found across six channel Reynolds numbers ranging from 1000 to 5000 to analyze how varying inlet conditions affects the optimal design. A set of optimal designs that maximizes heat transfer and minimizes pressure drop was identified, and a thermal stress analysis was performed on the optimal design. This work has developed a digital framework for the expedient topology design and evaluation of PCHE designs for gas-cooled microreactor applications. Correlations for the Nusselt number and Darcy friction factor were developed that can be useful for thermal hydraulic analyses using system codes. A thermal stress analysis was conducted and a brief discussion of the status of code cases of PCHEs for nuclear applications is given. Testing and thermomechanical modeling is needed to facilitate future code compliance of PCHEs for high pressure and high temperature applications.

42 ENGINEERING↗
DOE OSTI2025

Performance Evaluation of LPBF Manufactured 316H Components

This work represents the continuation of a benchmark study that includes modeling, fabrication and characterization as demonstration to support industry’s adoption of advanced manufacturing processes in a variety of structures. This comprehensive study investigated the feasibility of using additive manufacturing (AM) technologies, specifically Laser Powder Direct Energy Deposition (LP-DED) and Laser Powder Bed Fusion (LPBF), to produce complex nuclear microreactor components using 316H stainless steel. The research focused on manufacturing an expanded elbow pipe component with transitioning sections, which are traditionally difficult and costly to produce through conventional manufacturing methods. The overall study’s primary objectives are therefore demonstrating AM viability for nuclear applications, optimizing process parameters, developing comprehensive material characterization protocols, validating computational modeling approaches, and establishing manufacturing guidelines for complex geometries. Although the initial work included the phased approach of cubical, upscaled cylindrical components, it is to enable to obtain more knowledge for the printing of the expanded elbow structure. The project achieved significant progress in process development by successfully optimizing LP-DED parameters to achieve 99.16-99.97% relative density in 316H stainless steel components. Through systematic evaluation of sixteen cube samples with varied laser powers (400-700W) and scan speeds (600-900 mm/min), optimal processing windows were identified at 500-550W with 600-700 mm/min or 650-700W with 650-900 mm/min scan speeds. The DED manufactured 316H demonstrated mechanical properties comparable or superior to wrought materials, with Young's modulus ranging from 153-208 GPa and controlled microstructural characteristics including greater than 95% face-centered cubic (FCC) phases and engineered cellular structures with sizes between 3.23-6.17 µm.

36 MATERIALS SCIENCE↗
DOE OSTI2024

High-temperature structure, elasticity, and thermal expansion of ε-ZrH 1.8

Zirconium hydride is a promising candidate material for nuclear microreactor applications as a solid-state moderator component, owing to its favorable neutronics properties and good thermal stability over other metal hydrides. Here, in the present work, the crystal structure, thermal expansion, and elastic properties of the hydrogen-rich ε phase hydride were measured at elevated temperatures in the range 300–900 K. Samples were prepared by direct hydriding Zircaloy-4 metal – a nuclear-grade zirconium alloy. Room-temperature lattice parameters agree well with those reported from literature for unalloyed zirconium hydride and fall within an observed quadratic H-content dependence. The coefficients of thermal expansion, determined from lattice expansion and dilatometry, agree well within our work but were about 30 % lower than those reported by others for unalloyed hydrides. Density functional theory-based molecular dynamics simulations were used to compare with thermal expansion and elasticity measurements. Results showed lattice parameter temperature dependence and slope of thermal expansion align with those from measurements. Based on diffraction scans at select temperatures, ε phase remained stable in air up to at least 770 K. Likewise, dilatometry showed smooth thermal expansion up to the thermal decomposition temperature around 950 K. The precise decomposition temperature was not determined via diffraction due to sparse scanning. The complete elastic property measurements were gathered for ε-phase Ziracloy-4 hydride for the first time. Young's modulus was lower compared to the metal and δ hydride phases. High-temperature elasticity measurements were limited to <350 K due to acoustic dissipation effects.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Capacity optimization of nuclear power integration to meet dynamic industrial demand

To decarbonize their industrial facilities, The Dow Chemical Company has collaborated with Idaho National Laboratory (INL) to study the integration of nuclear power with an industrial chemical facility. Using Holistic Energy and Resource Optimization Network developed at INL for optimizing and analyzing integrated energy systems, a nuclear microreactor system was sized and evaluated for dynamic dispatch to Dow Silicones Corporation’s Carrollton, KY (USA) site for iloxane production. It was found that a 180 MW th system (12 × 15MW th ) with 75.1 MWh th of thermal energy storage could provide heat and power to the chemical facilities. In the process, this would reduce electricity imports by 99.9 % and reduce the Scope 1 and 2 emissions of the site by 292,100 tonnes CO 2 /yr (98.8 %). The primary novelty of this work is a first of a kind design and optimization of a microreactor powered integrated energy system to provide heat and power to a chemical plant using real plant data. This analysis will pave the way for future studies using dispatchable clean energy sources to reduce carbon emissions and commodity industries’ reliance on fossil fuels.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Modeling and Optimization of a Nuclear Integrated Energy System for the Remote Microgrid on El Hierro

Nuclear microreactors are a potential technology to provide heat and electricity for remote microgrids. There is potential for the microgrid on the island of El Hierro to use a microreactor, within an integrated energy system (IES), to generate electricity and provide desalinated water. This work proposes a workflow for optimizing and analyzing IESs for microgrids. In this study, an IES incorporating a microreactor, thermal energy storage (TES) system, combined heat and power plant, and a thermal desalination plant was designed, optimized, and analyzed using Idaho National Laboratory’s Framework for Optimization of Resources and Economics (FORCE) toolset. The optimization tool, Holistic Energy Resource Optimization Network (HERON), was used to determine the optimal capacity sizes and dispatch for the reactor and thermal energy storage systems to meet demand. The optimized reactor and TES sizes were found to be 11.61 MWth and 58.47 MWhth, respectively, when optimizing the IES to replace 95% of the island’s existing diesel generation needs. A dynamic model of the system was created in the Modelica language, using models from the HYBRID repository, to analyze and verify the dispatch from the optimizer. The dynamic model was able to meet the ramp rates while maintaining reactor power with minimal control adjustments.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Functional and Operating Requirements for the Microreactor Agile Non-Nuclear Experimental Test Bed (MAGNET)

Microreactors, or small, transportable reactors with a capacity of < 20 MWTH, are sought to provide heat and power for myriad applications in remote areas, military installations, emergency operations, humanitarian missions and disaster relief zones as illustrated in Figure 1. These small, transportable reactor designs, while offering many advantages, are largely untested and unproven. System and component testing is needed to demonstrate to regulators that these designs are safe and to convince customers that the systems are robust, reliable, and efficient. The microreactor agile non-nuclear experimental test bed (MAGNET) is being constructed at Idaho National Laboratory to assist with the development, demonstration, and validation of microreactor components and systems. MAGNET will support technology maturation to reduce uncertainty and risk relative to the operation and deployment of this unique class of systems. Stakeholders for this test bed include microreactor developers, energy users, and regulators. Regulators will be engaged early in the design and testing to expedite regulatory approval and licensing. Within MAGNET, systems and components can be safely tested, providing valuable information on operating regimes, failure modes, and thresholds. Since there are various types of microreactors being proposed, which can be classified according to their core cooling method, heat-pipes, gas-cooled (pebble bed or prismatic), molten salt, light water, or light water, the goal is to provide a test bed that is broadly applicable to multiple microreactor concepts. Each reactor type poses a different set of design and operational challenges and performance claims stated by commercial vendors have not been independently verified through rigorous testing. The initial set of tests to be performed in MAGNET are targeted towards demonstrating the feasibility and performance of heat-pipe cooled reactors, since this concept is unique to very small nuclear reactors. However, the testbed will be constructed to accommodate other designs in addition to heat-pipe cooled reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Sockeye: A One-Dimensional, Two-Phase, Compressible Flow Heat Pipe Application

Sockeye is a heat pipe analysis application based on the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element framework. The primary purpose of Sockeye is to provide a transient heat pipe simulation tool to be used in the analysis of nuclear microreactor designs. Sockeye provides the capability to perform one-dimensional, two-phase, compressible flow simulation of a heat pipe working fluid and two-dimensional, axisymmetric heat conduction for the heat pipe cladding and its surroundings. Sockeye is demonstrated against analytical solutions and experimental data from the SAFE-30 heat pipe module test.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Topology optimization of an airfoil fin microchannel heat exchanger using artificial intelligence

High-performance microchannel heat exchangers are needed to supply heat for power conversion for nuclear microreactors. An airfoil fin microchannel design, constructed of Alloy 617 with helium as the working fluid, is analyzed and optimized using a design of experiments with artificial intelligence techniques. The use of airfoil fins offers the potential to reduce pressure drop across the heat exchanger, as compared to other types of channel configurations. A framework for topology optimization of airfoil fin printed circuit heat exchangers (PCHEs) has been developed that can be readily extended to different fin sizes and shapes, as well as different inlet and operating conditions, materials of construction, and working fluids. An optimization procedure is developed that employs computational fluid dynamics for a set of design points identified using Latin hypercube sampling. Computational fluid dynamics is used to analyze a simplified two-channel configuration where five design parameters are varied – inlet angle, fin scale, extent of staggering, transverse and longitudinal pitches. Two methods (a 5D polynomial and a regression neural network) are compared for generating surrogate models and the resulting response surface approximation is input to a genetic algorithm that is used to identify a set of optimal parameters. The optimal geometries are found across six channel Reynolds numbers ranging from 1000 to 5000, since inlet conditions affect flow through the heat exchanger. Additionally, a set of optimal designs that maximizes heat transfer and minimizes pressure drop is identified, and a thermal stress analysis is performed on the optimal design. Correlations for the Nusselt number and Darcy friction factor are developed that can be useful for thermal hydraulic analyses using system codes. Thermal stresses are analyzed and a brief discussion of the status of code cases of PCHEs for nuclear applications is given. Testing and thermomechanical modeling is needed to facilitate future code compliance of PCHEs for high pressure and high temperature applications.

42 ENGINEERING↗