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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

PANDA-FES: Portable and Adaptable Neutron Diagnostics for Advancing Fusion Energy Science

Nuclear fusion is a potential source of carbon-free electricity with many concepts in development. The Portable and Adaptable Neutron Diagnostics for Advancing Fusion Energy Science (PANDA-FES) suite has been deployed since 2021 to measure neutron yield, energy, and spatiotemporal source location at two different Z-pinch fusion devices. This diagnostic can be used at a variety of facilities pursuing fusion in the magnetic, inertial, and magneto-inertial regimes. These different regimes have a wide range of time scales from less than 100 ns to a few μ s, neutron yields from 10 6 to 10 11 , and noise environments. Neutron yield is measured through activation of 79 Br and 89 Y with calibrated detectors. Temporal, spatial, and energy dependence of neutrons is measured with scintillators coupled to photomultiplier tubes (PMTs). Experimental setups and data analysis methods have been developed for these conditions. Finally, neutron yield, neutron energy anisotropy, and spatiotemporal evolution of the source have been measured.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Porosity in nuclear graphite and its impact on nuclear reactor science and criticality safety applications

Porosity in nuclear-grade graphite significantly influences its low-energy neutron scattering, yet its effect on underlying phonon properties remains debated. Here, this work integrates inelastic and small-angle neutron scattering (INS/SANS) experiments, advanced atomistic simulations with a novel machine-learned potential (DeepMD), total cross-section measurements, and neutronics calculations (SCALE, MCNP, OpenMC) to investigate porosity’s impact on neutron thermalization. INS measurements on diverse graphite grades reveal no discernible porosity effect on phonon spectra, which align with crystalline graphite. Conversely, total cross-section data below ≈10 meV show increased scattering attributable to SANS. Our DeepMD simulations demonstrate that realistic micropores do not distort phonon spectra, challenging the assumptions in current ENDF/B-VIII.1 porosity thermal scattering laws (TSLs). These TSLs, based on random atom removal, produce unphysical phonon spectra and inflate inelastic cross-sections. Augmenting a crystalline TSL with an SANS component accurately captures experimental total cross-sections. Neutronics benchmarks (ICSBEP/IRPhE) show ENDF porosity TSLs unphysically increase neutron multiplication factor, keff. Crucially, incorporating SANS physics (NCrystal/OpenMC) indicates accurately modeled porosity negligibly affects keff, reactor physics, or criticality safety.

Critical benchmarks↗
DOE OSTI2025

Assessing fuel cycle design options for advanced microreactors

Microreactor (MR) technology have recently gained traction due to their reduced construction cost compared to traditional large reactors. Their small physical geometry results in increased neutron leakage and deteriorated neutron economy which limits the achievable burnup of MR fuel. Refueling strategy currently discussed in MR design community is the battery-like refueling which is involve replacing the entire reactor core at the end of their operational cycle. Here, this paper investigates partial core refueling as means to increase MR fuel burnup and improve fuel cycle economy as a result. Two fuel cycle design strategies have been successful. These are the partial core refueling and partial core refueling combined with assembly rotation. Both strategies have been tested to operate a heatpipe-cooled MR referred to as the eVinci-like core for 72 Effective Full Power Months (EFPMs). The partial core refueling showed to reduce the refueling requirements by 18% compared to the battery-like refueling strategy. This corresponds to 10.5% reduction in the Net Present Value (NPV) of fuel cost over the 72 EFPMs of operation. The partial core refueling combined with rotation case reduces the refueling requirements by 29% (corresponding to 14.5% reduction in NPV of fuel cost) compared to the battery-like refueling strategy.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI1968

Nuclear Physics Made Very, Very Easy

The fundamental approach to nuclear physics was prepared to introduce basic reactor principles to various groups of non-nuclear technical personnel associated with NERVA Test Operations. NERVA Test Operations functions as the field test group for the Nuclear Rocket Engine Program. Nuclear Engine for Rocket Vehicle Application (NERVA) program is the combined efforts of Aerojet-General Corporation as prime contractor, and Westinghouse Astronuclear Laboratory as the major subcontractor, for the assembly and testing of nuclear rocket engines. Development of the NERVA Program is under the direction of the Space Nuclear Propulsion Office, a joint agency of the U. S. Atomic Energy Commission and the National Aeronautics and Space Administration. This report is being reprinted for use in the U. S. Atomic Energy Commission and National Aeronautics and Space Administration educational and technology utilization programs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

SAFARI - Secure Automation For Advanced Reactor Innovation (Final Technical Report)

The Secure Automation For Advanced Reactor Innovation (SAFARI) project was a pioneering initiative aimed at fundamentally changing how nuclear power plants are operated and maintained. Recognizing that current nuclear plants often rely on extensive manual procedures and large staffs, leading to higher costs compared to other energy sources like natural gas, SAFARI sought to introduce smart, automated technologies to make nuclear energy more efficient, cost-effective, and safer. This report details the research and development efforts of the SAFARI project, bringing us closer to a future where advanced nuclear reactors can operate more autonomously, adapt flexibly to energy demands, and predict their maintenance needs before issues arise. One of the key achievements of the SAFARI project is its contribution to our understanding of how Artificial Intelligence (AI) and sophisticated computer models, known as Digital Twins, can be effectively integrated with the complex physics of nuclear reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Selection of Sampling and Surrogate Modeling Methods for State-Point Evaluations of an AGN-201M Reactor

Nuclear reactor digital twins (DTs) have been proposed for use as a safeguards technology to efficiently monitor new and novel reactors as they come online. A safeguards DT needs to be capable of detecting misuse and diversion as they occur, requiring physics models to be accurate and efficient. Mathematical surrogate models are capable of achieving the necessary efficiency and can largely maintain the accuracy of higher-order models given a quality training sample. The Multiphysics Object-Oriented Simulation Environment (MOOSE) code framework is specifically equipped to generate training samples and create surrogate models using full-order reactor physics models. Utilizing an operational AGN-201M reactor’s specifications, two surrogate types were trained on samples of variable size, and using Cartesian products, Latin hypercube sampling, and quadrature sampling, each was compared and evaluated on accuracy when compared to a full-order Monte Carlo model. Both surrogate types were able to capture reactivity changes within 0.05 $ of the Monte Carlo model while reducing the computation costs by eight orders of magnitude.

MOOSE↗
DOE OSTI2024

Multi-physics Modeling of Radiative Heat Transfer and Fluid Flow for the Reactor Cavity Cooling System

High-temperature gas-cooled reactors (HTGRs) are notable for their high thermal efficiency and potential for combined heat and power applications. These reactors are particularly appealing due to their advanced passive safety features. HTGRs utilize passive safety systems that function without requiring active components like pumps or compressors during emergencies. These reactor designs depend on a Reactor Cavity Cooling System (RCCS) to manage decay heat removal from the reactor pressure vessel (RPV) during accident conditions. The RCCS consists of vertical rectangular channels known as "risers" or riser ducts positioned around the RPV. These risers receive heat from the RPV through both convective and radiative heat transfer mechanisms. Understanding the interplay of multiple physical phenomena, such as fluid dynamics, heat transfer, and neutron interactions, is essential for the effective design and operation of nuclear reactors, particularly for systems like the RCCS. Multi-physics simulations provide a comprehensive approach to studying these interactions, offering detailed insights and enhancing accuracy. They are especially important in RCCS designs, where the interaction between radiative and convective heat transfer can significantly impact system performance. By leveraging multi-physics simulations, complex reactor behaviors can be modeled without compromising the fidelity of the underlying physical processes. This work aims to establish a robust methodology for coupling multiple physical processes in an air-cooled RCCS. By focusing on validating this multi-physics approach, the study involves designing test cases that simulate various conditions to verify the numerical models employed. The outcomes of this research will provide critical insights for accurately modeling and optimizing complex nuclear systems like the RCCS.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Deployment and performance of a Low-Energy-Threshold Skipper-CCD inside a nuclear reactor

Charge Coupled Devices (CCD) are being used for reactor neutrino experiments and have already demonstrated their potential in constraining new physics models. The prospect of a Skipper-CCD experiment looking for standard and beyond standard model (BSM) physics in a nuclear reactor has been evaluated for different benchmark scenarios. Here, we report the first installation of a 2-g Skipper-CCD inside the containment building of a 2 GW th nuclear power plant and analyze its performance throughout its first 18 months of operation. The sensor was successfully deployed at Atucha II, in Argentina, 12 meters away from the center of the reactor core. We discuss the challenges involved in the commissioning of the detector and present data acquired during reactor ON and reactor OFF periods, with the sensor functioning with a sub-electron readout noise of 0.17 e - . Based on an exposure of 56.8 g day reactor ON and two reactor OFF data sets with a total exposure of 118.1 g day we characterize the system and evaluate the sensitivity to CEvNS. We achieved a background rate of 33 kdru and a low threshold of 45 eV ee . The ongoing efforts to improve sensitivities to CEvNS and BSM interaction are also discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Impact of High-Reactivity Advanced Test Reactor Experiments on Photon Heating in Nearby Experiment Locations

The Advanced Test Reactor’s (ATR’s) distinctive ability to provide a wide range of irradiation conditions is attractive for programs pursuing fuel qualification experiments. These potentially high-fuel-load experiments are a relatively new development and produce unexplored effects on nearby experiments. Here, this paper explores how photon heating of such an experiment may affect other nearby experiment programs, ultimately serving to better inform decisions regarding experiment design and risks to programmatic goals. The MC21 (Monte Carlo for the 21st Century) code is used to model and study how gamma heat generation rates and axial effects impact different ATR positions. The results reveal that the proximity of a given experiment’s position to the high-fuel-load one can significantly alter that experiment’s expected axial profile.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Simulating the effect of grain structure and porosity on creep for powder bed fusion 316H

This report details results from modeling studies focused on identifying the potential factors influencing creep performance of 316H stainless steel manufactured using Laser Powder Bed Fusion (LPBF), with a focus on experimentally-observed and predicted differences between the response of the AM material and conventionally manufactured wrought 316H. The studies presented here systematically look at the role of grain structure, porosity and texture in the anisotropic creep behavior of the material under conditions expected in high temperature advanced nuclear reactors. A physics-based Crystal Plasticity Finite Element modeling approach has allowed us to look at these factors in isolation and study their role in the material's long-term deformation behavior. An update to the precipitation model used in the constitutive framework for 316H is also presented here, with the aim of improving the accuracy of our results from this modeling effort. This work is a step in the direction of gaining mechanistic understanding of the long-term deformation behavior of LPBF 316H, helping us model its long term performance and reducing the qualification time for the material.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Application of a Physics-Informed Convolutional Neural Network for Monitoring the Temperature Fields in High-Temperature Gas Reactors

Here, this work presents current advances in applying a physics-informed convolutional neural network (CNN) to evaluate temperature distributions in advanced reactors. Our goal is to demonstrate that the CNN can reconstruct temperature fields within the solid region of a prismatic fuel assembly in a high-temperature gas reactor (HTGR) with sensor data available in only a few cooling channels. Before that, we showcase the superior performance of the physics-informed CNN in comparison to a purely data-driven multilayer perceptron (MLP), considering a canonical heated channel setup. This analysis shows the advantages of our approach and justifies its choice. The datasets employed here are obtained upon numerical simulations performed with codes under the Nuclear Energy Advanced Modeling and Simulation program. This work is important, as industry experience indicates that the assembly material in HTGR concepts is prone to large thermal-mechanical loads nearing operational limits. This makes it crucial to characterize peak temperatures and their distributions near hot spots. Modern thermocouples are unreliable in these types of harsh environments because of the high neutron fluxes and elevated temperatures involved. The CNN-based field reconstruction represents an attractive solution, enabling sensor arrays in less aggressive locations and augmenting indirect predictions for less accessible regions. The results show that the CNN reduces prediction errors by orders of magnitude in comparison to the MLP, considering the simple yet well-representative heated channel case. In the case of the HTGR fuel assembly, the CNN can successfully reconstruct temperature fields over various cooling regimes. Furthermore, we also explore the algorithm’s ability to detect abnormalities. Interestingly, the CNN proves it has the capacity to detect blockage in one of the noninstrumented cooling channels.

Machine learning↗
DOE OSTI2024

Bayesian Analysis of TRISO Fuel: Quantifying Model Inadequacy, Incorporating Lower-Length-Scale Effects, and Developing Parallel Active Learning Capabilities

The U.S. Department of Energy (DOE)’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program aims to develop predictive capabilities by applying computational methods to the analysis and design of advanced reactor and fuel-cycle systems. This program has been providing engineering-scale support for the continued development of BISON, a high-fidelity, high-resolution fuel performance tool. Fuel behavior in nuclear reactors is governed by a complex network of mechanisms that interact with various other physics aspects in the reactor system. Any model developed to represent fuel behavior will likely be idealized, resulting in uncertainties when comparing their predictions against the observed data. In Fiscal Year (FY)-23, we initiated the Uncertainty Quantification (UQ) work by using Bayesian methods to establish a level of model trustworthiness and further improve it, with a particular emphasis on TRI-Structural isOtropic (TRISO) nuclear fuel. This year, we further expanded on that UQ work by investigating an approach to quantifying model inadequacy and accounting for lower-length scale (LLS) effects in TRISO silver (Ag) release modeling. Furthermore, we are implementing parallel active learning capabilities to reduce the computational cost (i.e., required computational resources and elapsed time) of performing UQ. Specifically, we utilized The Kennedy O’Hagan framework for Bayesian uncertainty quantification (KOH) to account for model inadequacy in TRISO Ag release predictions made by BISON. The KOH framework represents an improvement over the standard Bayesian framework used in FY-23. Explicitly accounting for model inadequacy in the Bayesian framework helps establish the level of experimental noise uncertainty in the Advanced Gas Reactor (AGR) data. We compared the inverse UQ results obtained from both the standard Bayesian and KOH frameworks in light of the AGR-2/3/4 data, and also compared the predictive UQ results obtained from these two frameworks in light of the AGR-1 data. Next, we investigated the impact of considering LLS effects in the Ag release simulations. We developed an expanded database of LLS simulated effective diffusivities for Ag, covering a wide range of microstructures and temperatures. Using this database, we developed a framework for incorporating LLS effects into the engineering-scale Ag release UQ. We developed both parametric and non-parametric approaches for bridging the length scales. We then investigated the inverse UQ results in light of the AGR-2/3/4 data and the predictive UQ results in light of the AGR-1 data, and compared the LLS-informed approach and the Arrhenius equation, which does not include microstructure information. Finally, we discussed implementing parallel active learning capabilities in the Multiphysics Object Oriented Simulation Environment (MOOSE)/BISON to reduce the computational cost (i.e., computational resources and elapsed time) of Bayesian UQ. For verification purposes, we first tested these new capabil ities on a species interaction problem. We then demonstrated them on the TRISO Ag release application, showing that parallel active learning capabilities can enhance the accuracy of UQ while also substantially reducing the computational cost in comparison to the reference methods developed in FY-23.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

A methodology for domain overlapping coupling of thermal-hydraulic systems

Multi-scale coupling has increasingly drawn attention as a promising approach for modeling thermal systems. Traditional system codes provide fast and robust predictions at the plant scale, while high-fidelity computational fluid dynamics (CFD)-based tools resolve localized flow and heat transfer phenomena with greater accuracy. By combining these complementary strengths, co-simulations enable multi-scale analysis that would otherwise be computationally prohibitive for a standalone CFD code. Here, this work introduces a robust and problem-agnostic domain overlapping (DO) coupling between the system thermal-hydraulic (STH) code System Analysis Module (SAM) and the coarse-mesh CFD code Pronghorn. Both applications belong to the Comprehensive Reactor Analysis Bundle (BlueCRAB) code suite, a code suite in active development at the Idaho National Laboratory (INL), tailored for multi-physics analysis of advanced reactors. Unlike previous approaches, BlueCRAB supports an agnostic interface between codes based on different fidelity, while its coupling formulation can address arbitrary flow geometries with multiple inlets and outlets in coupled components. The implemented method leads to consistent pressure drops, enthalpies, and scalar concentrations between coupled SAM and Pronghorn simulations. The methodology is demonstrated through two verification tests, which ensure the numerical consistency and conservation across the codes, and through one validation test against experimental data. The proposed problems explore different physical aspects inherent to thermal systems, with particular attention given to nuclear reactor analysis. These include buoyancy-driven flows, complex flow patterns, and setups with multiple inlets and outlets, representing challenges in advanced reactor applications.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

At-power subcritical multiplication in the Advanced Test Reactor during nuclear requalification testing

Power division information during nuclear requalification of the Advanced Test Reactor (ATR) is of considerable interest as an importance function for observed changes to core reactivity. The degree to which a given physical subdivision of a critical reactor acts as a neutron source for other lobes is not analytically characterized for general application. When ATR operates at power, individual power-producing lobes rely on each other as neutron sources in order to maintain constant power, which in general requires either exactly critical multiplication within a reactor or an external neutron source. Here, this work shows that fuel element and lobe powers in ATR can be related with subcritical multiplication theory. Subcritical multiplication factors are computed with a physically validated analytical method based on actual at-power operation, quantifying for each lobe its dependence on other lobes as an external neutron source. This explanation is significant for ATR due to the desire to irradiate a large variety of experiments simultaneously, each having its impact on the core neutron population. For any physical subdivision of any other critical reactor, it is likewise true that the subdivision undergoes only subcritical multiplication.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2026

Radiological Releases from Novel Fuel Forms in Advanced Reactors During Severe Accidents for Consequence Analyses

Various advanced reactor developers are exploring the potential for reductions in the size of physical security forces and emergency planning zones. These reductions are based on robust fuel forms and inherently safe reactor designs. However, such reductions in physical protection measures could increase the risk of sabotage. To assess the possibility of reducing these measures, sabotage-induced radiological consequence analyses were carried out. These analyses considered accident scenarios that were beyond design basis accidents and overly conservative (Shah, 2025a; Shah, 2025b; Shah and Hartanto, 2026), yielding very large release fractions. These fractions, which can be used to evaluate physical protection and emergency planning requirements, have been crudely determined and applied as demonstrations for a sodium-cooled fast reactor (SFR) (Shah and Hartanto, 2025a), a high-temperature gas-cooled reactor (HTGR) (Shah and Hartanto, 2025b), a heat pipe–cooled reactor (HPR) (Shah and Hartanto, 2025c), and a molten salt–cooled reactor (MSR) (Shah et al., 2026). A Sandia National Laboratories (SNL) team used MELCOR—a fully integrated severe accident analysis code—to demonstrate the code’s capability to analyze advanced (i.e., not light water–cooled) reactors (including a fluoride salt–cooled high-temperature reactor [FHR]) and calculate radiological releases to the environment during severe accidents (Wagner et al., 2022a, 2022b, 2022c, 2023a, and 2023b). Although the analyses were carried out to demonstrate MELCOR’s growing capability, the release source terms were estimated for advanced reactors, providing valuable insights into the accident progression and radiological releases. These findings from prior SNL studies, including estimated source terms and related sensitivity studies, were leveraged to derive source terms for postulated sabotage-induced accidents. Insights from these sensitivity studies informed the scaling of SNL’s estimated source terms for the defined accident scenarios. The derived release fractions for the severe accident scenarios for the respective reactor designs can be used to perform more nuanced dose consequence analyses to evaluate the reactors’ physical protection and emergency planning zone requirements. These analyses are in accordance with the risk-informed, performance-based approach proposed under 10 CFR Part 53. This study builds on the prior source term analyses and associated sensitivity studies by SNL to derive time-dependent and design-informed release fractions. Section 2 describes the diverse advanced reactor designs analyzed by the SNL team. Section 3 discusses the severe accident analyses, the release fractions calculated, and the limitations and assumptions of the demonstration project. Section 4 presents the release percentages derived for the hypothetical sabotage-induced severe accidents at the advanced reactors. Section 5 summarizes the study’s findings and conclusions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Assessment of the Impact of Realistic Sensor Physics and the Integration of Ex-Core Sensors on Reactor Power Synthesis

In the work documented in this report, a weighting function–based core power synthesis method was applied to multiple Monte Carlo N-Particle (MCNP) reactor models, which are informed based on simulated self-powered neutron detector (SPND) responses. The weighting function method used has been coined the point-based iterative (PBI) method. The goal of this application is to assess the impact of considering realistic sensor physics in the generation of the simulated SPND outputs as well as to consider how the synthesis is impacted based on the inclusion of ex-core detectors in the model. The NuScale small modular reactor (SMR) and Westinghouse AP1000 pressurized water reactor (PWR) are the models that served as the testbeds for the assessment of realistic sensor physics; this was achieved by using Geant4 SPND models in comparison with analytical models, such that the effect of electron transport in realistic SPND geometries in the Geant4 model can be understood in terms of synthesis error and convergence time. The comparison was considered for fuel burnup–induced perturbations, for a range of sensor string densities and synthesized power distribution axial fidelities. The Texas A&M Testing, Research, Isotopes, General Atomics Reactor (TAMU TRIGA) reactor MCNP model was used to assess the impact of ex-core sensors; this was done by performing synthesis with and without the ex-core detectors and by quantifying the synthesis error and number of iterations associated with Gaussian-type perturbations in many locations in the core. The TAMU TRIGA model was particularly pertinent for this study because of the interest in future experimental tests with SPNDs in this reactor, as well as the ease of modifying the MCNP model to include ex-core detectors with heterogeneously described response functions. Results from the comparison between the Geant4 and analytical SPND models indicate that similar average and maximum synthesis errors were obtained for burnup-induced perturbations in both the NuScale SMR and the AP1000. This was true for a range of sensor string densities and axial fidelities. However, there were marked differences between both the Geant4 and analytically informed models in terms of the iterations required to converge on the synthesized power distribution. Namely, the Geant4-informed models tended to lead to fewer iterations, except for a few sensor–core configurations that had particularly numerous iterations. Results from the ex-core sensor assessment with the TAMU TRIGA model indicate that the inclusion of ex-core sensors drastically reduces the synthesis error of Gaussian-type perturbations close to the edge of the core, and it slightly reduces synthesis errors for perturbations closer to the center of the core. This was achieved with a minimal increase in computational cost—that is, the number of iterations required for convergence. The errors were identified to be in the same location as the perturbation in the core, indicating that the methodology remains robust for unperturbed regions of the core. A secondary result from this study with the TAMU TRIGA was yielded by analysis of the neutron flux levels in the in-core and ex-core sensor locations of the core; these flux levels indicate that SPNDs could be used as both in-core and ex-core sensors, so long as the emitter material is sensitive to thermal neutrons. The results from these studies provide a quantitative understanding of the importance of considering realistic sensor physics and including ex-core sensors to perform accurate and timely power distribution synthesis of a reactor core.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

SPARC - Plans for a New Critical Experiment Facility with a Horizontal Split Table

Several critical experiment facilities, sometimes referred to as zero power reactor facilities, have provided crucial data to aid understanding and validate nuclear-physics models since the beginning of nuclear technology. Indeed, the first man-made reactor, Chicago Pile-1, was essentially this type of reactor. However, there was a downturn in nuclear technology development toward the turn of the millennium, and the need for these specialized research facilities waned. Now there are few of these experimental facilities operational in the world and those that remain have relatively small critical assembly machines. The need for criticality safety benchmark experiments at intermediate neutron energy levels and the modern resurgence of interest in advanced reactors designs, many of which do not have historical precedents in terms of nuclear fuel composition, moderator, and coolant combinations, all combine to create a substantial need for a critical experiment facility with a large horizontal split-table (HST) machine. A HST machine is used to arrange two separate and subcritical parts of a core assembly, bring them together in a precise manner to achieve criticality using remote controls, and separate them to achieve a subcritical configuration again. A new effort was recently performed to develop user needs for a HST, assess candidate locations at the Idaho National Laboratory (INL), and develop a plan for deployment. This project is referred to as the System Physics Advanced Reactor Critical facility (SPARC). A few months after this assessment began, and shortly after as a viable pathway was emerging, a series of important presidential executive orders were issued to revitalize nuclear energy in the United States (U.S.). The relevance of SPARC to these executive orders was immediately apparent. The far-reaching potential of SPARC to these executive orders will reside in its ability to produce data which facilitates licensing of advanced nuclear reactor designs while reducing uncertainties to help increase energy production alongside new criticality safety data to enable more efficient nuclear fuel manufacture, transport, and storage.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗