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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Release on the Virtual Test Bed of an MSRE thermal hydraulics model

The nuclear industry is taking leaps in innovations with companies seeking a sustainable energy future through advanced nuclear reactors. The \gls{DOE}’s \gls{neams} program seeks to substantiate and bolster the deployment of advanced reactors through flexible multifidelity, multiphysics simulations of advanced nuclear reactors. Applications like SAM for one-dimensional systems thermal-hydraulics, and Pronghorn for multidimensional coarse mesh thermal-hydraulics, are geared to support innovations in industry by facilitating design, optimization, and licensing of advanced nuclear reactors. Coupling systems thermal-hydraulics and computational fluid dynamics codes can be difficult as the pressure coupling converges slowly; however, it is important to obtain the desired accuracy in each part of the primary loop. The authors of this model created an \gls{odc}~\cite{Mau23} approach to coupling SAM and Pronghorn. Leveraging this coupling technique, a \gls{msre} model was developed and released to the \gls{neams}/\gls{nric} \gls{vtb}. The \gls{msre} was chosen to be modeled because of the wealth of experimental data available and because of the strong physics coupling between the core and primary circuit \cite{doi:10.13182/NT8-2-118}. This document contextualizes the history of the \gls{msre}, describes the thermal hydraulics models used, and detail the implementation of multidimensional thermal-hydraulics and system codes based on the \gls{odc} method~\cite{Penn} for the \gls{msre} model. Finally, this document presents how other modelers could apply the SAM-Pronghorn \gls{odc} for other advanced reactor models.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Optimization of Integrated Energy Systems

Integrated energy systems that couple nuclear power plants with additional products including hydrogen, storage, or synthetic fuels provide a more flexible energy source that can be more economical than generating electricity alone. Determining the size and shape of these systems and optimizing their operation is challenging. INL, through the IES program, has developed optimization software to help solve these challenges. Holistic Energy Resource Optimization Network (HERON) is a software tool to optimize the size and capacity of integrated energy systems using stochastic optimization. Optimization of Real-time Capacity Allocation (ORCA) is a software tool under development to perform real-time economic optimization of these systems using economic model predictive control. An overview of these tools and a discussion of their optimization methods will be presented in this talk.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Enhancing Monte Carlo Workflows for Nuclear Reactor Analysis with Metamodel-Driven Modeling

Monte Carlo codes are essential components of many reactor physics simulation workflows as high-fidelity continuous-energy neutron transport solvers. Among Monte Carlo radiation transport codes, MCNP is particularly notable due to its diverse simulation capabilities, large user base, and long validation history. Despite being a powerful simulation tool, MCNP provides limited capabilities to allow automated execution, model transformation, or support for user-defined logic and abstractions that limit its compatibility with modern workflows. Here, to better integrate MCNP into a modern scientific workflow, we have developed an intuitive yet full-featured MCNP Application Program Interface (API) in Python, named MCNPy, which provides a specialized set of classes for MCNP input development. Moreover, to guarantee that our reading, writing, and modeling capabilities remain self-consistent (and to render the huge scope of the MCNP API manageable), we have adopted a strategy of model-driven software development in which a generalized model of the MCNP input format has been created. From this generalized model, or “metamodel,” problem-specific implementations such as an engine for input validation or a codebase for programmatic operations may be automatically generated. Since MCNPy primarily acts as a Python front-end to the underlying Java API that directly interfaces with the metamodel, it is intrinsically linked to the metamodel and thus remains maintainable. With MCNPy, users can programmatically read, write, and modify any syntactically valid MCNP input file regardless of its origin. These capabilities allow users to automate complicated tasks like design optimization and model translation for nuclear systems. As examples, this work demonstrates the use of MCNPy to find the critical radius of a plutonium sphere and to translate a 9000+ line MCNP input file into a corresponding OpenMC model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

PRO-X Fuel Cycle Transportation and Crosscutting Progress Report

The PRO-X program is actively supporting the design of nuclear systems by developing a framework to both optimize the fuel cycle infrastructure for advanced reactors (ARs) and minimize the potential for production of weapons-usable nuclear material. Three study topics are currently being investigated by Sandia National Laboratories (SNL) with support from Argonne National Laboratories (ANL). This multi-lab collaboration is focused on three study topics which may offer proliferation resistance opportunities or advantages in the nuclear fuel cycle. These topics are: 1) Transportation Global Landscape, 2) Transportation Avoidability, and 3) Parallel Modular Systems vs Single Large System (Crosscutting Activity).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Openpronghorn

OpenPronghorn is a simulation tool specifically tailored for modeling thermal-hydraulic phenomena in advanced nuclear reactors. It is built on the Multiphysics Object-Oriented Simulation Environment (MOOSE), an open-source platform that facilitates the development of high-performance scientific computing applications. OpenPronghorn solves the Navier-Stokes equations, which describe the conservation of mass, momentum, and energy in fluid flows, using the finite volume numerical method. The code supports a wide range of fluid flow conditions that are applicable to nuclear reactors, including incompressible and weakly compressible flows, as well as single-phase and multiphase flows. It is capable of modeling diverse flow regimes, including laminar and turbulent flows, using various turbulence models such as the standard k-epsilon models, the v2f model, and the mixing length model. For multiphase flows, OpenPronghorn employs a mixture a Eulerian modeling approach with mixture, drift-flux, and full Eulerian models, and includes open-sourced interfacial transfer correlations for drag, exchange, and heat transfer coming from the scientific literature. OpenPronghorn's modular design allows it to handle multiscale simulations, ranging from detailed Reynolds-Averaged Navier Stokes (RANS) simulations to coarse-mesh and lumped parameter models. This flexibility enables users to perform high-fidelity simulations of specific reactor components as well as system-level analyses of entire reactor circuits. The code can be coupled with other MOOSE-based tools using the MultiApp system, allowing for the transfer of coupling quantities such as mass flow rates, heat fluxes, and boundary conditions between different simulation scales. One of the main features of OpenPronghorn is the it includes built-in validation cases from the open-source scientific literature and supports the implementation of user-defined models and correlations through MOOSE's FunctorMaterial system. OpenPronghorn is designed to be computationally efficient, leveraging the SIMPLE projection method for large-scale problems, and can be run on high-performance computing systems to handle the extensive computational demands of detailed reactor simulations. Overall, OpenPronghorn is a versatile and robust tool that provides critical insights into the thermal-hydraulic behavior of advanced nuclear reactors, supporting the design, safety, and optimization of next-generation nuclear energy systems.

Retamales, Mauricio Eduardo Tano [Idaho National L↗
DOE OSTI2023

Modeling nuclear energy’s future role in decarbonized energy systems

Increased attention has been focused on the potential role of nuclear energy in future electricity markets and energy systems as stakeholders target rapid and deep decarbonization and reductions in fossil fuel use. This paper examines models of electric sector planning and broader energy systems optimization to understand the prospective roles of nuclear energy and other technologies. In this perspective, we survey modeling challenges in this environment, illustrate opportunities to propagate best practices, and highlight insights from the deep decarbonization literature on the range of visions for nuclear energy's role. Nuclear energy deployment is highest with combinations of stringent emissions policies, nuclear cost reductions, and constraints on the deployment of other technologies, which underscores model dimensions related to these areas. New modeling capabilities are needed to adequately address emerging issues, including representing characteristics and applications of nuclear energy in systems models, and to ensure the relevance of models for policy and planning as deeper decarbonization is explored.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Integrating an Ensemble Reward System into an Off-Policy Reinforcement Learning Algorithm for the Economic Dispatch of Small Modular Reactor-Based Energy Systems

Nuclear Integrated Energy Systems (NIES) have emerged as a comprehensive solution for navigating the changing energy landscape. They combine nuclear power plants with renewable energy sources, storage systems, and smart grid technologies to optimize energy production, distribution, and consumption across sectors, improving efficiency, reliability, and sustainability while addressing challenges associated with variability. The integration of Small Modular Reactors (SMRs) in NIES offers significant benefits over traditional nuclear facilities, although transferring involves overcoming legal and operational barriers, particularly in economic dispatch. This study proposes a novel off-policy Reinforcement Learning (RL) approach with an ensemble reward system to optimize economic dispatch for nuclear-powered generation companies equipped with an SMR, demonstrating superior accuracy and efficiency when compared to conventional methods and emphasizing RL’s potential to improve NIES profitability and sustainability. Finally, the research attempts to demonstrate the viability of implementing the proposed integrated RL approach in spot energy markets to maximize profits for nuclear-driven generation companies, establishing NIES’ profitability over competitors that rely on fossil fuel-based generation units to meet baseload requirements.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Economic Evaluation of a Coupled Nuclear Power Plant and Hydrogen Production Facility: A Case Study

This study optimized the design sizes and operation of a power-to-hydrogen-to-power integrated energy system to allow a baseload power plant to operate flexibly in the energy market. In collaboration with a utility industry partner, the system, consisting of an electrolyzer, compressors, storage tank, and fuel cell, was optimized under conditions specific to the proposed project at the site of a nuclear power plant. The Design Integration and Synthesis Platform to Advance Tightly Coupled Hybrid Energy Systems (DISPATCHES) maximized net present value by optimizing sizing of components and dispatch decisions. Revenues included sale of electricity, capacity payments typical of the New York Independent System Operator, and the section 45V hydrogen production tax credit of the Inflation Reduction Act of 2022 (the tax credit was assumed to be available to legacy plants in the absence of clear guidance at present). Under default assumptions which excluded many capital expenditures, the base case optimized solution had a net present value of $\$$1.4 million over a 30 year lifetime, with a 0.365 MW fuel cell operating nearly continuously and 85% of revenues supplied by the hydrogen production tax credit (which was counted as a revenue regardless of profit, thus assuming credit monetization or offset of taxes within the larger firm was possible in all years). Beyond the base case, a sensitivity study elucidated drivers of the economics as capacity payment rate and hydrogen production tax credit rate vary. Additional sensitivity studies also extended results to variation of other, previously fixed parameters, including the fuel cell capital cost, and to imposition of further constraints. Optimization was also repeated for the default assumptions but recognizing tax credits upon use of hydrogen rather than upon its production, producing no change in the optimal solution. Most notably, capacity payments above $\$$15/kW-month drove optimal fuel cells multiple times larger than those with the default estimated capacity payment of $\$$2.5/kW-month (approaching 11 vs. 0.365 MW), and these larger fuel cells operated rarely (capacity factors of ~0.03). Furthermore, when the hydrogen production tax credit was provided for only 10 years, under the specific assumptions of this study (e.g., neither site preparation costs nor electrolyzer capital cost counted), the optimal solution avoided economic loss by ceasing system operation after the 10th year. Viewed broadly, this study demonstrated the capabilities of DISPATCHES, which can be user-adapted to serve other industrial case studies.

08 HYDROGEN↗
DOE OSTI2024

Advanced manufacturing and digital twin technology for nuclear energy*

Advanced manufacturing techniques and digital twin technology are rapidly transforming the nuclear industry, offering the potential to enhance productivity, safety, and cost-effectiveness. Customized parts are being produced using additive manufacturing, automation, and robotics, while digital twin technology enables the virtual modeling and optimization of complex systems. These advanced technologies can significantly improve operational efficiency, predict system behavior, and optimize maintenance schedules in the nuclear energy sector, leading to heightened safety and reduced downtime. However, the nuclear industry demands the highest levels of safety and security, as well as intricate manufacturing processes and operations. Thus, challenges such as data management and cybersecurity must be addressed to fully realize the potential of advanced manufacturing techniques and digital twin technology in the nuclear industry. This comprehensive review highlights the critical role of digital twin technology with advanced manufacturing toward nuclear energy to improve performance, minimize downtime, and heighten safety, ultimately contributing to the global energy mix by providing dependable and low-carbon electricity.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Alchemy: A Model-Based Approach for 2D to 3D Autonomous Nuclear System Design

Engineering design of nuclear power plant (NPP) piping and equipment systems frequently bypasses crucial 2D system planning, instead moving straight to 3D modeling. This often leads to designs that exceed building envelope constraints, forcing expensive and time-consuming redesigns. When 2D modeling is employed, it typically involves labor-intensive manual workflows that convert 2D drawings into 3D models, resulting in inefficiencies and errors across design iterations. These workflows further suffer from poor software interoperability and dependence on proprietary software ecosystems, thereby contributing to schedule delays and cost overruns. This paper presents Alchemy, an autonomous framework that transforms 2D system definitions into Industry Foundation Classes (IFC)-compliant 3D building information models (BIMs) for expediting nuclear facility design at the conceptual preliminary phase. Using a model-based approach, the framework treats the 2D system diagram as the central reference model employed to automatically generate all subsequent outputs, ensuring consistency between the system definition and the resulting physical design. A web-based interface enables engineers to define hierarchical system topologies including associated equipment, geometric properties, and connectivity requirements. A two-phase equipment layout optimization algorithm automatically computes collision-free spatial configurations within predefined building envelopes. An artificial intelligence (AI)-assisted pipe routing module then generates orthogonal, collision-free routing paths, allowing the user to select either an A* search-based method or an Ant Colony Optimization (ACO)-based method. All outputs are authored natively in IFC format, relying on open-source technologies and standardized formats in order to ensure extensibility and eliminate proprietary software dependencies. The proposed framework is validated on two representative pressurized-water reactor (PWR)-based case studies, for which it autonomously generates IFC-compliant 3D models in minutes, drastically reducing workflows that typically require hours of manual effort. The generated model demonstrates topologically correct equipment placement, physically plausible spatial relationships, and collision-free pipe routing consistent with known PWR loop configurations. This work represents a foundational step toward digital engineering for nuclear facility preliminary design, with future ongoing development targeting design code compliance and expanded system complexity.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Analysis of Multi-Output Hybrid Energy Systems Interacting with the Grid: Application of Improved Price-Taker and Price-Maker Approaches to Nuclear-Hydrogen Systems

The growing recognition of the value of hydrogen as an energy intermediate in supporting future power systems with high shares of variable renewable energy has prompted many studies to quantify the economic potential of multi-output hybrid systems, which are one type of integrated energy systems (IES). Because of the complexity of modeling multiple sectors, these studies typically use simplified modeling approaches to capture the interactions between sectors. In this study, we explore the implications of alternative modeling approaches for nuclear-hydrogen IES focusing on a power system in the Midwest United States. We combine highly resolved capacity expansion and production cost modeling tools of the power system with a detailed hydrogen system optimization tool to determine the optimal electrolyzer and storage sizing and optimal operations of the nuclear-hydrogen hybrid resource across three future study years. We compare economic and operational outcomes across a spectrum of modeling approaches, including a non-hybridized base approach; a traditional price-taker approach that does not include the impact of hydrogen production on the electricity system; a power-system-focused price-maker approach that does not account for temporal hydrogen constraints; and two improved price-taker and price-maker approaches that each address the impact of revenue-optimal levels of electricity production on the resulting power system and temporal hydrogen constraints on the overall feasible solution. Results show how a traditional price-taker approach can overestimate the economic benefits of multi-output nuclear-hydrogen IES compared to our two improved approaches that estimate both hydrogen system constraints and power system interaction. We find that hydrogen output requirements and storage size limits are key drivers to overall operations and some economic outcomes. Under our assumed constant hydrogen output requirement, storage costs, test system, and modeling approaches, our results indicate that hybridization can provide a net benefit, but results are sensitive to the treatment of hydrogen revenues and electricity prices as impacted by the power system evolution.

capacity expansion modeling↗
NASA NTRS1990

Lunar orbiting microwave beam power system

A microwave beam power system using lunar orbiting solar powered satellite(s) and surface rectenna(s) was investigated as a possible energy source for the Moon's surface. The concept has the potential of reduced system mass by placing the power source in orbit. This can greatly reduce and/or eliminate the 14 day energy storage requirement of a lunar surface solar system. Also propellants required to de-orbit to the surface are greatly reduced. To determine the practicality of the concept and the most important factors, a zero-th order feasibility analysis was performed. Three different operational scenarios employing state of the art technology and forecasts for two different sets of advanced technologies were investigated. To reduce the complexity of the problem, satellite(s) were assumed in circular equatorial orbits around the Moon, supplying continuous power to a single equatorial base through a fixed horizontal rectenna on the surface. State of the art technology yielded specific masses greater than 2500 kg/kw, well above projections for surface systems. Using advanced technologies the specific masses are on the order of 100 kg/kw which is within the range of projections for surface nuclear (20 kg/kw) and solar systems (500 kg/kw). Further studies examining optimization of the scenarios, other technologies such as lasers transmitters and nuclear sources, and operational issues such as logistics, maintenance and support are being carried out to support the Space Exploration Initiative (SEI) to the Moon and Mars.

Fay, Edgar H.↗
NASA NTRS1990

Lunar orbiting microwave beam power system

A microwave-beam power system using lunar orbiting solar-powered satellite(s) and surface rectenna(s) is investigated as a possible energy source for the moon's surface. The concept has the potential of achieving reduced system mass by placing the power source in orbit. This can greatly reduce and/or eliminate the 14-d energy storage requirement of a lunar surface solar system. Also, propellants required to de-orbit to the surface are greatly reduced. To determine the practicality of the concept and the most important factors, a zeroth-order feasibility analysis is performed. Three different operation scenarios employing state of the art technology and forecasts for two different sets of advanced technologies are investigated. To reduce the complexity of the problem, satellite(s) are assumed to be in circular equatorial orbits around the moon, supplying continuous power to a single equatorial base through a fixed horizontal rectenna on the surface. State of the art technology yields specific masses greater than 2500 kg/kw, well above projections for surface systems. The specific masses are on the order of 100 kg/kW using advanced technologies, which is within the range of projections for surface nuclear (20 kg/kW) and solar systems (500 kg/kW). Further studies examining optimization of the scenarios, other technologies, such as laser transmitters and nuclear sources, and operational issues, such as logistics, maintenance, and support, are being carried out to support the Space Exploration Initiative (SEI) to the moon and Mars.

Fay, Edgar H.↗
DOE OSTI2021

Development of MCNP Training Modules for Safeguards Practitioners [Abstract]

The Monte-Carlo N-Particle (MCNP) software developed at LANL is the most widely used neutron transport code in the world. It is an essential tool for a variety of applications including detector development and design, nuclear fuel burnup simulation, criticality safety, and nondestructive assay system optimization. For this reason, it is indispensable within the safeguards and materials control & accountability (MC&A) communities. Multiple MCNP training courses have been created and taught over the last several decades by the MCNP development team at LANL, however there are no existing courses that cover specialized topics considered fundamental to NDA and safeguards models. To fill this gap, the MCNP team and Safeguards Science and Technology group at LANL have co-created a set of training modules customized to meet the specialized needs of the safeguards and MC&A communities. The basic modules cover concepts such as NDA system optimization, He-specific and other capture tallies, and tools for improved theoretical understanding. An advanced module was also created to cover topics including variance reduction for active interrogation simulations, use of the LANL MCNPTools post-processor, PTRAC (particle tracking) and list-mode data simulations, and fuel burnup simulations. The training modules teach to the latest and most state-of-the-art MCNP features and tools released by the development team at LANL and are intended to be taught jointly by the developers and safeguards experts. Ultimately, we hope that creation of these modules will serve to capture and convey the safeguards modeling and MCNP expertise at LANL, and that we will be able to share the modules more broadly with the MC&A and safeguards communities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Quantifying Uncertainty of Deep Reinforcement Learning Based Decision Making for Operations and Maintenance of Nuclear Power Plant

This paper summarizes research that integrates condition monitoring and prognostics with decision making for nuclear power plant operations and maintenance. As part of this research, we have developed an online asset management tool to help reduce life-cycle maintenance and repair costs. Using the latest advancements in condition monitoring, supply chain analytics, and deep reinforcement learning, we have created a predictive maintenance tool that can optimize the maintenance and spare-part management of a repairable nuclear system. To demonstrate these methods, preliminary studies were conducted on a simple, representative maintenance system undergoing a stochastic degradation process that requires repairs or replacement to continue operation. Through Monte Carlo simulations, we were able to reduce maintenance spending by approximately 50% compared to optimized, time-based maintenance strategies. Not only does the decision maker reduce the average life-cycle costs, it also minimizes the chance of high cost scenarios, lowering the variance of the expected cost distributions, and reducing overall financial risk. Furthermore, this work also studies the ability of the decision maker to handle various levels of noise from observation uncertainty. By introducing uncertainty into the decision-making process, we have quantified the robustness and resiliency of the decision maker, as well as identified necessary levels of observability to demonstrate cost effectiveness.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2007

High Fidelity Thermal Simulators for Non-Nuclear Testing: Analysis and Initial Results

Non-nuclear testing can be a valuable tool in the development of a space nuclear power system, providing system characterization data and allowing one to work through various fabrication, assembly and integration issues without the cost and time associated with a full ground nuclear test. In a non-nuclear test bed, electric heaters are used to simulate the heat from nuclear fuel. Testing with non-optimized heater elements allows one to assess thermal, heat transfer, and stress related attributes of a given system, but fails to demonstrate the dynamic response that would be present in an integrated, fueled reactor system. High fidelity thermal simulators that match both the static and the dynamic fuel pin performance that would be observed in an operating, fueled nuclear reactor can vastly increase the value of non-nuclear test results. With optimized simulators, the integration of thermal hydraulic hardware tests with simulated neutronie response provides a bridge between electrically heated testing and fueled nuclear testing, providing a better assessment of system integration issues, characterization of integrated system response times and response characteristics, and assessment of potential design improvements' at a relatively small fiscal investment. Initial conceptual thermal simulator designs are determined by simple one-dimensional analysis at a single axial location and at steady state conditions; feasible concepts are then input into a detailed three-dimensional model for comparison to expected fuel pin performance. Static and dynamic fuel pin performance for a proposed reactor design is determined using SINDA/FLUINT thermal analysis software, and comparison is made between the expected nuclear performance and the performance of conceptual thermal simulator designs. Through a series of iterative analyses, a conceptual high fidelity design can developed. Test results presented in this paper correspond to a "first cut" simulator design for a potential liquid metal (NaK) cooled reactor design that could be applied for Lunar surface power. Proposed refinements to this simulator design are also presented.

Bragg-Sitton, Shannon M.↗
DOE OSTI2024

Performance analysis of integrated Nuclear-Solar Energy system sharing same molten salt thermal energy storage

Advanced nuclear reactors may be deployed with integrated thermal energy storage to improve flexibility and maximize revenue. This presents opportunities for thermal integration with concentrating solar power (CSP) to generate component synergies and/or improve performance. Here in this study, a computational model is developed for an integrated nuclear and CSP system that both share the same molten salt thermal energy storage (TES). Optimized dispatch schedules are developed subject to various market conditions, and the ratio of the nuclear to CSP thermal output is also varied. Performance of the combined system is compared to separate nuclear and solar plants, to determine if there is an overall benefit that can be derived from sharing the TES. Given sufficient volatility in electricity prices (e.g., under CAISO market conditions), synergies of up to 8% in net revenue are observed as a result of sharing the same TES, primarily due to improved revenue from enabling operation of the turbine closer to its design point, as well as being able to better take advantage of higher electricity prices. The synergy benefits are largest when the nuclear and solar plants have similar thermal output. However, when prices are less volatile the opposite behavior can be observed and it can be preferable to operate the nuclear plant as a baseload generator.

14 SOLAR ENERGY↗