Search NASA⌕ Search

SEARCH · Search NASA

Results for “Reactor system design”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Irradiation Experiments and Thermal Analysis for Reactor System Design and Analysis at INL

Idaho National Laboratory (INL) is the nation's lead nuclear laboratory working to enhance reactor systems' safety, security, economics, and efficiency. Research and development (R&D) programs at INL support the current fleet of nuclear reactors for safer operation and newer reactors technology design, development, demonstration, and deployment. A major focus of INL's mission is the reactor system design and analysis supported by the irradiation experiments and thermal analysis of advanced and current-generation nuclear fuels and materials. The irradiation experiments and thermal analysis provide a deeper understanding of basic radiation damage processes that can determine the basis for performance improvements and verification of modeling assumptions. These experiments and analyses include experiment management: design, fabrication, characterization, irradiation, and post-irradiation examination. This research involves thermal, neutronic, and material investigation using the INL's Advanced Test Reactor (ATR) and Transient Reactor Test (TREAT) facilities. The results from these experiments and analysis are required to develop the regulatory basis for deploying new or modified fuels and materials. This seminar talk will also provide a general overview of the INL's research facilities, ongoing research programs, core capabilities, and opportunities for students and faculties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Cyber threat assessment of machine learning driven autonomous control systems of nuclear power plants

We report advanced cyber-attacks against critical infrastructure and the energy sector are becoming more common. With the invention of autonomous control systems (ACS) within advanced nuclear reactor designs, system designers, reactor operators, and regulators must consider cybersecurity during the design and operational phases. This article provides a cyber threat assessment of machine learning (ML)-based digital twinning (DT) technologies in the context of advanced reactor ACS. A cyber–physical testbed was created to emulate nuclear reactor digital instrumentation and controls (I&C) and act as a basis for the ACS. The ACS was designed as two plant-level DTs predicting reactor malfunctions and determining control actions and two component-level DTs responsible for classifying component states and forecasting component inputs and outputs (I/O). Two duplicate ACS designs– one using a traditional ML framework and one using an automated ML (AutoML) framework– were created and tested against cyber-attacks on training data, real-time process data, and ML model architectures to determine their respective qualitative cyber-risk in terms of likelihood and impact. Both frameworks showed similar cyber-resilience against training, real-time, and ML architecture attacks, proving that neither is inherently more secure. Recommended safeguard and security measures are posed to system designers, reactor operators, and regulators to maintain the cybersecurity of ML-based DT technologies such as ACS, prompting a holistic view of shared responsibility for maintaining cyber-secure ML-based systems.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Autonomous System Inference, Trojan, and Adversarial Reprogramming Attack and Defense (Final)

In the world of ever-advancing technology, Autonomous Systems (AS) find extensive application, bolstering functionalities of critical infrastructures such as nuclear power plants. These systems, however, are increasingly becoming a target for nefarious activities, namely through inference attacks, trojan attacks, and adversarial reprogramming. This paper delves into a comprehensive exploration of machine learning (ML)-driven autonomous control systems within advanced nuclear reactor designs, revealing the vulnerabilities and proposing strategies for defense against potential cyber-attacks. Advanced cyber-attacks against critical infrastructure and the energy sector are becoming more common. With the invention of autonomous control systems (ACS) within advanced nuclear reactor designs, system designers, reactor operators, and regulators must consider cybersecurity during the design and operational phases. This article provides a cyber threat assessment of machine learning (ML)- based digital twinning (DT) technologies in the context of advanced reactor ACS. A cyber-physical testbed was created to emulate nuclear reactor digital instrumentation and controls (I&C) and act as a basis for the ACS. The ACS was designed as two plant-level DTs predicting reactor malfunctions and determining control actions and two component-level DTs responsible for classifying component states and forecasting component inputs and outputs (I/O). Two duplicate ACS designs– one using a traditional ML framework and one using an automated ML (AutoML) framework– were created and tested against cyber-attacks on training data, real-time process data, and ML model architectures to determine their respective qualitative cyber-risk in terms of likelihood and impact. Both frameworks showed similar cyber-resilience against training, real-time, and ML architecture attacks, proving that neither is inherently more secure. Recommended safeguard and security measures are posed to system designers, reactor operators, and regulators to maintain the cybersecurity of ML-based DT technologies such as ACS, prompting a holistic view of shared responsibility for maintaining cyber-secure ML-based systems. As global reliance on generation III reactors begins to be critically assessed, the evolution towards advanced reactor systems utilizing digital instrumentation and controls (I&C) becomes not merely preferable, but essential. The integration of semi and fully autonomous control systems (ACS), powered by digital I&C and machine learning (ML)-based digital twinning (DT) technologies, emerges as a potent strategy to mitigate operations and maintenance costs, thereby enhancing the economic feasibility of novel reactor designs. However, with a staggering 500% and 380% increase in cyber-attacks reported against the energy sector by the United States Department of Energy (DoE) and the European Union respectively, a surge in cyber vulnerabilities specifically targeting the nuclear industry has been 2 markedly observed. Notable incidents, such as the W32.Ramnit spyware infiltration at the Gundremmingen nuclear power plant in Germany and the Dtrack spyware intrusion at the Kudankulam nuclear power plant in India, while not directly compromising core industrial control systems (ICS), underscore a compelling necessity to fortify cybersecurity protocols in safeguarding reactor systems against increasingly adept digital adversaries. In light of this, our investigation extends beyond conventional cybersecurity parameters, diving into the intricate web of potential vulnerabilities woven into ML-based DTs and ACS in advanced reactor systems. A crafted cyber-physical testbed and preliminary ACS were devised to act as a mirror, reflecting potential configurations of advanced reactor control designs. Moreover, this study is intertwined with a scrutinization of ML models, developed either through conventional, manually tuned methodologies or via automated means through AutoML, probing into their cyber-risk profiles within operational technology (OT) environments. Expanding on this, two distinct ACS blueprints were forged – one navigating through the corridors of traditional ML and the other traversing the path of AutoML – in an effort to holistically encapsulate the considerations pivotal to ML-based DT control system design. Employing the SANS Institute Industrial Control System (ICS) Kill Chain and the MITRE ATT&CK Tactics, Techniques, and Procedures (TTP) framework, a structured analysis was conducted, launching three targeted attacks against the training dataset, real-time dataset, and ML models, therein dissecting the potential cyber-attack implications against both ML frameworks within an ACS milieu. It is essential to note that three distinct categories of attacks were conducted against both ACS configurations, each encompassing three distinct ML-based DTs, cumulating in a total of 18 varied attacks. This exploration extends into the realms of Autonomous System Inference, Trojan, and Adversarial Reprogramming Attack and Defense, unraveling vulnerabilities, and opportunities for fortified defenses against such intrusions, particularly where ML-driven technologies, and by extension, ACS, are deployed. Final recommendations, articulated through a lens of security, safeguard, and implementation considerations, are presented for both traditional and AutoML models, anchoring upon the existing knowledge landscape and ML-based DT modeling for ACS, and are offered as a beacon to guide the nuclear industry through the intricate cybersecurity challenges that lie ahead.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Uncertainty Propagation from Experiment Measurements to Modeling Approaches: A Case for SMR Steam Entrainment Testing

To license new and advanced reactor designs, regulators must be convinced that their unique safety cases—relative to existing large scale reactors—have been adequately addressed by the designed reactor protection systems. In water cooled small modular reactors (SMRs), droplet entrainment in steam flow has significant implications on the progression of accident scenarios due to its compact design features, which requires representative test data applicable to SMR designs. Computer code, modeling and simulation (M&S) tools and models require adequate verification, assessment, and qualification. This includes M&S results validation against scaled empirical data within allowable uncertainty bands to gain regulatory approvals during the various stages of reactor system design, demonstration, and commercialization. However, measurement uncertainty within the empirical datasets and test data applicability ranges requires careful consideration of M&S inputs (i.e., boundary conditions, and initial conditions), and verification and validation efforts. This study focuses on uncertainty quantification in designing scaled test facilities for SMR applications with appropriate measurements and a standard data-reduction method to estimate thermal hydraulics characteristics parameters that incorporate physics phenomena of interest. In addition, this study supports the evaluation model development and assessment process using M&S that interfaces with advanced computing tools and digital twin capabilities. This will allow synchronization between experiment and modeling approaches for droplet entrainment testing and analysis, improving diagnostics, prognostics, and decision-making to accelerate regulatory approval.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Towards an Agent-Based Blackboard System for Reactor Design Optimization

The field of reactor design is rich with opportunities for applications of computational optimization algorithms; these applications can range from preliminary core design to reactor shuffling patterns. Many of these schemes rely on sets of previously generated solutions (sometimes referred to as “generations”) to inform future decisions. While it is important to build upon prior knowledge, this process requires a full generation of solutions to be formed before future solutions can be examined. Rather than relying on a generational scheme to perform an optimization, we propose using an agent-based approach in conjunction with a blackboard framework for performing reactor design optimizations. Utilizing an agent-based approach allows agents to perform tasks independently, while retaining the ability to build off of previous solutions. We develop an agent-based blackboard system (ABBS) for determining the Pareto front (PF) in sodium fast reactor design optimization problems and compared this with the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). Our goal is to evaluate the viability of the ABBS in producing a PF that is comparable with the NSGA-II algorithm. The design space consists of the fuel height, fuel smear, and plutonium fraction in the core, and we seek to minimize the reactivity swing and plutonium mass, while maximizing the burnup. The diversity, coverage, and spread of the PFs generated by the two methods are examined, and the ABBS is able to converge to the same PF as the NSGA-II algorithm. These results show that the ABBS is able to find optimal designs that are similar to those found by the NSGA-II algorithm. We conclude our study by applying the ABBS to the design of a sodium-cooled fast reactor to dispose of weapons-grade plutonium. The ABBS finds a core design that can burn upwards of 17.5 kg of weapons-grade plutonium per year and degrade an additional 195 kg of weapons-grade plutonium per year into non-weapons-grade material.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Optimization Modeling for Advanced Syngas to Olefin Reactive Systems

Reactor designs with mixed catalysts play an important role in transforming a multiple reactor system to single-shot reactors. In addition to savings in capital and ease of implementation, single-shot reactors are useful to break equilibrium limitations, thereby increasing the yield and selectivity of desired product as shown in previous studies. However, the nonlinear and highly exothermic nature of mixed-catalyst systems makes it difficult for commercial process simulation and optimization tools to optimize these systems. This study describes the development and application of optimization strategies for mixed-catalyst, single-shot reactors for syngas to olefin (STO) processes. Finding the optimal catalyst distribution is challenging and requires advanced solution strategies for singular optimal control problems, which are poorly conditioned and often lead to flat response surfaces. The graded bed and partial-moving finite-element approaches are used to find the optimal catalyst distribution that maximizes the olefins yield. A 1.3% increase in the yield is observed from one zone to three zones. The yield further improves from three zones to the exact infinite dimensional solution by 0.2%. This improvement can be realized in practice by changing only the catalyst distribution, without any extra investment. Lastly, the results suggest that a mixed-catalyst single shot reactor bed can be applied to other reaction mechanisms to increase reactor performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Nuclear Space System Analysis and Modelling (NSSAM): A Software Tool to Efficiently Analyze the Design Space of Space Reactor Systems

Space reactors have the potential to play a key role in future NASA exploration activities due to their capability to enable sustainable power and advanced propulsion systems. To enable assessment of the space reactor design space, the nuclear space system analysis and modelling (NSSAM) software was developed by Analytical Mechanics Associates. NSSAM leverages a scalable and extensible software architecture which automates reactor analysis to perform coupled engine-reactor and reactor physics-thermal hydraulics calculations. This allows space reactor systems to be evaluated by a wider number of users with a consistent analysis approach to compare designs. NSSAM has been developed with multiple use cases to tailor the analysis to the level of detail desired by the user and computing resources. This summary overviews the NSSAM architecture and development approach, current capabilities (including design variants and use cases) and analysis approach for reactor and system component models.

nuclear thermal propulsion↗
DOE OSTI2023

Integral and Separate Effects Test Facilities To Support Water Cooled Small Modular Reactors: A Review

This study reviews previous experimental facilities and test programs relevant to water-cooled reactor system design and analysis to meet regulatory compliances. This study aims to find the best solution for designing the required experiments, obtaining necessary test data, and verifying the developed computer code/models to support the new reactor design and development while minimizing cost and time while leveraging experiences from previous facilities to minimize. Nuclear reactor licensing requires supportive design, analysis, and experimental results to ensure the safety of the full-scale prototype reactor in regular operation, as well as during postulated accident scenarios. These reactor design analyses are generally performed using system codes and other associated simulation tools that require assessment, verification and validation using an appropriate experimental dataset. Experimental facilities used for reactor system safety analysis and system code assessments are categorized into integral effects test (IET) and separate effects test (SET) facilities. Further, these IET and SET experiments and studies use geometrically scaled systems to reproduce the prototype system behavior at a reasonable cost, albeit with some scaling-related distortions. The design challenge of these model facilities is to identify and minimize scaling distortions while reproducing the most important operational phenomena in steady-state operation and in postulated accident scenarios. Lessons learned from previous experimental facilities, models, and correlations can support the development of new multipurpose, scaled, hybrid, integrated, and modular experimental facilities for advanced light water-cooled small modular reactors (SMRs). Successful operation of these facilities can significantly reduce upfront reactor development and demonstration costs and time to deployment.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Analysis of Postulated Accident Scenarios for the Transformational Challenge Reactor

The Transformational Challenge Reactor (TCR) is a helium-cooled, yttrium-hydride-moderated reactor that was designed for the U.S. Department of Energy Office of Nuclear Energy. A key objective of the TCR was to employ advanced manufacturing techniques in a nuclear system and demonstrate their potential for revolutionizing the nuclear reactor design process. One purpose of the present work is to demonstrate the safety of the TCR under postulated accidents. Based on RELAP5-3D and COMSOL analyses, the TCR remained below all current safety limits and far below the expected failure limits for the core materials. Another purpose of this work is to provide useful insights and recommendations regarding the application of RELAP5-3D to gas-cooled or other advanced reactors. A novel approach was implemented for simultaneously modeling conduction and radiation in RELAP5-3D, which was found to provide reasonable predictions of radial core, vessel, and ex-vessel heat transfer during postulated events. A multicode approach was also applied, in which high-fidelity COMSOL calculations were used to tune the radial heat transfer parameters in RELAP5-3D. The tuned RELAP5-3D model demonstrated comparable peak temperature predictions as COMSOL, despite a coarse treatment of the core in RELAP5-3D consisting of only two lumped heat structures. This high-fidelity tuning approach enabled enhanced accuracy as well as minimal complexity within the RELAP5-3D model, even for complex fuel geometric designs as in the TCR. Finally, investigations were made into the potential for flow reversal during a pressurized loss-of-forced-flow event in the TCR. The TCR is designed with downward helium flow through the core during normal operation. The RELAP5-3D model predicted that this downward flow would persist, without flow reversal, up to several days after the circulator trip. This was attributed to natural circulation hysteresis effects as have been noted in similar thermofluidic systems. Although flow stagnation and eventual reversal did not lead to unsafe TCR conditions, interesting spatial effects were observed which may have safety relevance for other reactor system designs and coolant types that are designed for downward core flow during normal operation, warranting closer investigation of the flow reversal phenomenon.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1972

Preliminary design of reactor power systems for the manned space base.

The results of design integration studies of uranium-zirconium hydride (UZr-Hx) reactor power systems for the NASA space base study program are presented. The power conversion systems investigated include the Brayton cycle, the organic Rankine cycle, the SNAP-8 mercury Rankine cycle, and thermoelectric (PbTe). The proposed space base has a 10-year life and requires 100 kWe of power. Two 50-kWe power systems with a nominal replacement life of 5 years are utilized. Parametric design data such as life, weight, radiator area, reactor outlet-temperature, reactor thermal power, and power conversion system efficiency are presented and used for the design and integration of the system with the space base.

Mckhann, G. G.↗
DOE OSTI2024

A machine-learning-aided data recovery approach for predicting multi-material thermal behaviors in advanced test reactor capsules

Instrumented experiments conducted at test reactors are essential to the deployment of new advanced reactor systems. Designing new experiments and generating data on specific reactor conditions require significant investments in terms of both time and cost. Finite element analysis software can be used to create high-fidelity models of experiment environments in order to support the actual experiments, but computation time remains a concern in terms of applying outcomes to real-time usage of data (e.g., a digital twin [DT]). Here, the present research proposes a machine-learning (ML) aided approach to making temperature and displacement predictions based on the thickness of the outer gas gap on the experimental capsule used for in-pile demonstration of a novel new thermal conductivity probe in the Advanced Test Reactor (ATR). This capsule consisted of U10Zr fuel, a rodlet, sodium, and inner and outer capsules. Gas gaps existed between the fuel and the rodlet, and between the inner and the outer capsule. The learning data pertained to an experimental capsule's radial distributions of temperature and displacement, as obtained based on Abaqus and the physical features. For the first step of ML sequence, the temperature was predicted using three positional parameters. Next, the displacement was predicted using seven additional parameters. Each physical feature was normalized in order to be both nondimensional and standardized. The temperature and displacement predictions showed good agreement with the simulation results in all cases involving interpolation and extrapolation. Furthermore, data similarity enhancement increased the similarity between the training and the target data, thereby increasing the predictive accuracy of the ML models. In certain extrapolation cases involving limited original ML model accuracy, data similarity enhancement and data recovery was able to somewhat improve this accuracy.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Accelerate Nuclear Research and Development by Reducing Time and Cost Spend in the Pre-conceptual Design Phase of Advanced Reactor Experiments

The design process of every new concept, such as advanced nuclear reactors or associated experiments, starts with the pre-conceptual design phase. In this phase, the viability of a wide range of design options needs to be assessed quickly, to understand the operating envelope and its feasibility. A variety of physics models (thermal-hydraulics, neutronics, mechanical design, etc.) has to be considered at this very first design stage and optimum component sizes and materials (e.g. heat exchangers, piping, turbomachinery, coolant type, etc.) have to be chosen for a given set of boundary conditions (e.g. heat source, heat sink, flow rate, etc.). Detailed solutions such as provided by high fidelity methods like computational fluid dynamics (CFD), Monte Carlo methods, etc. and even lower fidelity tools such as system or subchannel codes, etc. are usually not used during the pre-conceptual design due to the relatively long time needed to create input models, the computational time to obtain a solution and the lack of flexibility to quickly investigate different combinations of components, individual component sizes and material properties. High fidelity tools are usually only employed in the conceptual design and later phases once a base concept has been identified during the pre-conceptual design stage. The current practice during the pre-conceptual design stage is that analysts collect the needed equations, material properties, closure laws, etc. and create ad-hoc solutions form scratch for every new problem. There clearly is a lack of a flexible scoping tool that can be used during pre-conceptional design before higher fidelity tools (as described above) come into play. To reduce user errors in ad-hoc solutions and increase fidelity and efficiency, this project aims to investigate and develop a user-friendly scoping tool to address the thermal-hydraulic designing needs during preconceptual experiment design, i.e. Thermal-hydraulic Research Universal Scoping Tool (TRUST). The success of TRUST will provide the nuclear engineers with an easy-to-use and affordable calculator for early reactor system design and optimization.

42 ENGINEERING↗
NASA NTRS1991

Space nuclear power systems; Proceedings of the 8th Symposium, Albuquerque, NM, Jan. 6-10, 1991. Pts. 1-3

The present conference discusses NASA mission planning for space nuclear power, lunar mission design based on nuclear thermal rockets, inertial-electrostatic confinement fusion for space power, nuclear risk analysis of the Ulysses mission, the role of the interface in refractory metal alloy composites, an advanced thermionic reactor systems design code, and space high power nuclear-pumped lasers. Also discussed are exploration mission enhancements with power-beaming, power requirement estimates for a nuclear-powered manned Mars rover, SP-100 reactor design, safety, and testing, materials compatibility issues for fabric composite radiators, application of the enabler to nuclear electric propulsion, orbit-transfer with TOPAZ-type power sources, the thermoelectric properties of alloys, ruthenium silicide as a promising thermoelectric material, and innovative space-saving device for high-temperature piping systems. The second volume of this conference discusses engine concepts for nuclear electric propulsion, nuclear technologies for human exploration of the solar system, dynamic energy conversion, direct nuclear propulsion, thermionic conversion technology, reactor and power system control, thermal management, thermionic research, effects of radiation on electronics, heat-pipe technology, radioisotope power systems, and nuclear fuels for power reactors. The third volume discusses space power electronics, space nuclear fuels for propulsion reactors, power systems concepts, space power electronics systems, the use of artificial intelligence in space, flight qualifications and testing, microgravity two-phase flow, reactor manufacturing and processing, and space and environmental effects.

El-Genk, Mohamed S.↗
DOE OSTI2024

Planning for Material Control and Accountancy at Liquid Fueled Molten Salt Reactors

The purpose of this report is to provide molten salt reactor (MSR) developers and future US Nuclear Regulatory Commission (NRC) license applicants with recommendations for developing an effective and practical material control and accounting (MC&A) plan, focused primarily on MSR designs that use circulating liquid fuel. Because of the breadth of MSR designs, there is no single, generic, detailed MC&A plan that will work for every design. The wide variation of fresh fuel salts, the method and frequency of loading fresh fuel, the reactor system design components (e.g., tanks, filtration systems, chemical processing streams), and waste streams will determine the specific measurement locations and instrumentation that can best meet MC&A objectives throughout an MSR facility. Additionally, MSR designs are rapidly evolving, and new design features and deployment scenarios that will affect MC&A are being explored and pursued. This report defines a generic MC&A approach that was developed for terrestrial (as opposed to maritime) deployments to meet the intent of NRC domestic safeguards and MC&A. MSR license applicants should consider nuclear safeguards (both domestic and international) and security throughout the design, as early as the preconceptual design phase. MC&A of special nuclear material (SNM) is an aspect of the NRC’s domestic safeguards program, alongside physical protection. Because liquid-fueled MSRs are reactors with SNM in nondiscrete (or item) form, it is likely that the NRC may require liquid-fueled MSR license applicants to submit a formal MC&A plan as a part of their license application. Currently, the NRC licensing protocol presents a challenge because the NRC MC&A regulations have not been updated to accommodate advanced reactors, including types of MSRs. Because no liquid-fueled MSR has been licensed for operation at the time of this report, no template or precedence for a successfully licensed MSR MC&A plan exists. However, the MSR license applicant can take advantage of the NRC’s published commitments to performance-based regulations. The authors recommend that the license applicant, or MSR designers, develop an MC&A plan throughout the design lifecycle and plan to submit a detailed MC&A program description, or MC&A plan, to the NRC as a part of a license application. No MC&A plan template or guidance exists that is specific to liquid-fueled MSRs. The authors recommend that license applicants discuss the topic of MC&A during preapplication engagement. Because of the uniqueness of MC&A for liquid fueled MSRs, the authors recommend that liquid fueled MSR developers engage with the NRC on the topic of MC&A in the early phases of its design development and follow up any time there are significant modifications in design plans that would affect MC&A. For example, topics like modifications in fuel handling processes, changes in uranium enrichment, or additional chemical processing streams added to the design could be discussed with the NRC specifically on the topic of MC&A.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Accelerating nuclear-integrated data center pursuits in the USA: SWOT analysis, power-thermal management strategies and demonstration plan

Here, this study explores the increasing interest in leveraging nuclear power to meet the escalating energy demands of data centers in the United States (U.S.) by focusing on key factors that contribute to accelerated deployment. The study highlights the importance of N+1/N+2 power supplies (where N is the required number of units), outlines research and innovations in nuclear-integrated data center thermal management and demonstration plan. It also provides updates about status and costing of various reactor system designs. A summarized strengths, weaknesses, opportunities, and threats (SWOT) analysis shows the potential options for grid connectivity, reactors, and site selection. Suitable site discussions consider land and water availability, grid access, and optical fiber connectivity, and the study presents graded prospects for Department of Energy (DOE) sites with a specific example. Community engagement and partnerships are emphasized, particularly the roles of local government, federal agencies, utilities, and data center industry partners, which are crucial for accelerating deployment, business outreach, and approvals. The study provides actionable insights for stakeholders to accelerate the deployment of nuclear-powered data centers.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
NASA NTRS1991

Lunar in-core thermionic nuclear reactor power system conceptual design

This paper presents a conceptual design of a lunar in-core thermionic reactor power system. The concept consists of a thermionic reactor located in a lunar excavation with surface mounted waste heat radiators. The system was integrated with a proposed lunar base concept representative of recent NASA Space Exploration Initiative studies. The reference mission is a permanently-inhabited lunar base requiring a 550 kWe, 7 year life central power station. Performance parameters and assumptions were based on the Thermionic Fuel Element (TFE) Verification Program. Five design cases were analyzed ranging from conservative to advanced. The cases were selected to provide sensitivity effects on the achievement of TFE program goals.

Mason, Lee S.↗
NASA NTRS1973

The 5-kwe reactor thermoelectric system summary

Design of the 5-kwe reactor thermoelectric system was initiated in February 1972 and extended through the conceptual design phase into the preliminary design phase. Design effort was terminated in January, 1973. This report documents the system and component requirements, design approaches, and performance and design characteristics for the 5-kwe system. Included is summary information on the reactor, radiation shields, power conversion systems, thermoelectric pump, radiator/structure, liquid metal components, and the control system.

Vanosdol, J. H.↗