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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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DOE OSTI2024

Digital-Twin-Enabling Technologies for Online Condition Monitoring of Nuclear Power Plant Components

Online condition monitoring is an area of active research that may enable improved scheduling, maintenance, and safety of nuclear power plant components, reducing unnecessary derates while simultaneously improving operational capacity. Digital twins are one avenue to conduct online condition monitoring and are currently being explored by national laboratories and universities alike. Digital twins for online condition monitoring are, in essence, state concurrent models that emulate a physical process which predicts a parameter and compares it against a measured value. However, digital twins may also provide additional insights by combining and interpreting various sources of information. These insights may be used for preventative maintenance scheduling optimization or early fault detection and are projected to be valuable for meeting requirements under 10 CFR 50.55a. However, digital twin technologies are still under significant development; quantifying model uncertainties, improving unique fault identification, and multimodal sensor fusion are some areas under investigation. Therefore, in this work, we discuss and review the various enabling technologies, in the form of advanced sensors, instrumentation, and modelling methods, that may be used to implement and enhance digital twins for online condition monitoring. A potential use case for pump-motors is presented to demonstrate how these various pieces of enabling digital twin technologies may integrated together for online condition monitoring. Challenges and opportunities associated with the pump-motor digital twin enabling technologies are also identified and discussed.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications: Fourth Edition

As the world increasingly seeks low-carbon energy solutions, solar power emerges as the most abundant resource on our planet. However, the challenge of effectively harnessing this energy is crucial in the coming years. Solar energy applications such as photovoltaics, solar heating and cooling, and concentrating solar power use different technologies to capitalize on sunlight. Each system has unique capabilities and requirements, underscoring the need for reliable information about solar resources across diverse installations, from residential rooftops to large-scale power plants. This is especially important for substantial projects, often exceeding $1 billion in construction costs. Before embarking on such ventures, it is imperative to obtain accurate data concerning solar resource quality and reliability at specific sites. Developers require detailed historical information, including seasonal, daily, hourly, and, ideally, subhourly variability to effectively predict a power plant's annual performance. Without these vital data, financial analyses fall short. Moreover, with the growing adoption of distributed photovoltaics, integrating these generation sources becomes critical to maintaining grid reliability and stability. By accurately forecasting generation patterns, utilities and system operators can facilitate greater integration of solar energy, thus ensuring the operational stability of the grid. The complexity and importance of these issues have prompted the foremost experts in the field to collaborate under the auspices of the International Energy Agency's (IEA's) Photovoltaic Power Systems Programme (PVPS) Task 16 to publish this handbook, which summarizes state-of-the-art information about all these topics. The efforts focus on providing reliable data and insights that can help shape our investments in solar energy and drive a sustainable future.

14 SOLAR ENERGY↗
DOE OSTI2022

Front End Engineering Design of Linde-BASF Advanced Post-Combustion CO 2 Capture Technology at a Southern Company Natural Gas-Fired Power Plant (Final Scientific/Technical Report)

This document details the execution of Cooperative Agreement DE-FE0031847, “Front End Engineering Design of Linde-BASF Advanced Post-Combustion Carbon Dioxide (CO 2 ) Capture Technology at a Southern Company Natural Gas-Fired Power Plant” during the period of 10/1/2019 to 6/30/2022. The project was funded by the U.S. Department of Energy’s Office of Fossil Energy and Carbon Management (FECM) and managed by the National Energy Technology Laboratory (NETL). Southern Company Services, Inc. (SCS) was the prime recipient and led the project team. Other members of the project team included Linde, Inc. (Linde), Linde Engineering – Dresden (LED), and BASF. The overall goal of the project was to complete a front-end engineering design (FEED) study for installing the Linde-BASF post-combustion capture (PCC) technology at an existing domestic natural gas-fired combined cycle (NGCC) power plant within Southern Company’s portfolio of assets. The CO 2 capture plant was to be of commercial scale (at least 375 MWe) and include process units for pre-conditioning of the flue gas system, the CO 2 capture plant island, storage vessels, the CO 2 compression train, and any necessary components for integration into the NGCC plant. Mississippi Power’s Plant Daniel Unit #4 was chosen as the host site for the FEED with the target of capturing 90% of CO 2 emissions from the existing combustion turbines. The information produced by the FEED was used to develop a cost estimate of +/- 15% accuracy. Capital costs, excluding financing, are estimated at approximately $\$752$ million dollars (2021). The execution of a project based on this FEED study has an estimated duration of almost five years.

03 NATURAL GAS↗
DOE OSTI2022

SMART: Simplified Melting And Rotation-joint Technology

Oil based parabolic trough solar power plants are the most commercially mature CSP technology. However, the upper limit of about 400°C of the current organic heat transfer fluid(HTF)significantly limits the future potential of the technology. Advances in parabolic trough receiver and collector technology have enabled higher operating temperatures of potentially 500°C or above. The search for an improved higher temperature HTF has identified inorganic molten salts, specifically the mix referred to as Solar Salt, a 60:40 mix of sodium nitrate and potassium nitrate salt. However, Solar Salt starts to freeze at about 240°C. This poses a significant challenge for large parabolic trough plants that could have many kilometers of header piping and hundreds of kilometers of receiver piping all filled with molten salt. Plants using molten salt need to be designed to minimize the risk of freezing and to be able to recover from freeze events. Studies and field experiments have shown that this appears to be feasible and the approach appears to have strong economic advantages over conventional trough plants. However, some technical challenges remain related to the use of molten salt in trough solar fields, the cost of the freeze recovery system is significant, and many still question whether the risk of using molten salt is worth the economic upside. In our view, the potential economic upside justifies the continued look at molten salt HTF in parabolic trough plants. The objective of this project was to address the key technical issue remaining, look for opportunities to reduce the cost of the freeze recovery system, and improve the general information and tools available for assessing the design, performance and economics of trough plants using molten salt HTF.

14 SOLAR ENERGY↗
DOE OSTI2025

Using a Large Language Model for Accurate Technical Language Generation in the Predictive Maintenance of Circulating Water Systems in Nuclear Power Plants

Machine learning (ML) methods for predictive maintenance (PdM) are emerging as effective proactive strategies for diagnosing equipment degradation and enabling effective decision-making. However, explainability and trustworthiness of artificial intelligence are two salient challenges that need to be addressed for wider deployment of these technologies in nuclear power plants (NPPs). Large language models (LLMs) offer a unique approach to tackle these challenges by explaining PdM, work orders, diagnosis results, and ML algorithms to users, who may not be familiar with ML and PdM in general. Moreover, by dynamically retrieving relevant information from technical documents and evaluating factuality of LLM generation, the accuracy and relevance of LLM generations can be improved. This work demonstrates using LLMs to explain the causes and consequences of circulating water system failures based on multiyear NPP work orders. This work tests the capability of multimodal LLM approaches in explaining the differences in the circulating water system from both the Salem and Hope Creek NPPs using both text and image resources. This work also demonstrates the use of multimodal LLMs in describing the diagnosis tab of a predictive maintenance software named VIsualization for PrEdictive maintenance Recommendation (VIPER) to users.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

A 20-kW DC Oak Ridge Converter with Integrated AC & DC Sources for Grid Services and Energy Storage Systems

This paper proposes a wireless power transfer (WPT) platform with integrated energy conversion that has the capability for 1) recharging the energy storage systems (ESSs) from the grid systems, including renewable energy sources such as wind, solar, etc., 2) off grid systems recharging the ESSs from dc grid systems, 3) grid recharging of electric vehicles (EVs), and 4) off grid recharging of EVs from ESSs. The unique aspect of the method is the use of multi-interface power electronic converter for the grid and ESSs and EVs that can support a range of applications with ac / dc and dc / dc energy conversion ability in a single converter system. The key enabling technology to achieve these functionalities is Oak Ridge Converter (ORC) with polyphase coupler coil system both developed at ORNL. This new technology enables higher power density WPT systems while allowing the coils to interface from ac grid at 60 Hz frequency or dc source directly merging with 85 kHz operating frequency of switching component. The experimental results of the proposed system are presented for 20 kW output power with the system overall efficiency around 95.4% from dc source and 93% overall efficiency from ac grid achieving 9-10% current total harmonic distortion (THD) and 0.98-0.99 power factor (PF).

Asa, Erdem↗
DOE OSTI2020

Wireless Sensing and Communication Capability from In-Core to a Monitoring Center

Significant cost savings can be made if electrical cables can be replaced by wireless technology in current Nuclear Power Plants (NPP) and in advance reactor designs. Wireless technology can also provide in-core opportunities by significantly reducing the number of penetrations in the pressure vessel, cost and complexity of sensor installation and by increasing the efficiency of current and advanced reactors. Unlike other deployment scenarios for an industrial environment, operators need to have centralized control over all the networks. Centralized control will reduce implementation costs, provide single point control and enable monitoring of network devices, improve security, and enhance connectivity. Micro-sensors that can simultaneously monitor temperature and pressure within a fuel rod inside nuclear reactors will enable preventative actions during abnormal operating conditions. This ability could avert accidents and enable the expedient development of accident tolerant fuels. A novel micro-sensor suite (~ mm) to simultaneously measure multiple parameters such as temperature, strain, pressure, and neutron/gamma flux inside a fuel rod is being developed for use in reactors. The necessary communication architecture is also being developed to transmit measurement signals from the core to the plant's data cloud or control room. A three three-tier strategy has been developed to support wireless transmission of in-core measurements to the control room or to a secure cloud platform for control, analytics, and decision-making purposes. 1. In-core: data signal from in-core to outside of the pressure vessel within the containment building 2. Containment building: data signal from inside to the outside of the containment building and into the balance of the plant network 3. Balance of the plant network: information transmitted to the data cloud and control room This plan presents a wireless sensing and communication system for use within a reactor core and elsewhere. The communication technology is advantageous to compensate for network equipment failures and adverse data transmission conditions. Wireless technology will significantly increase the resiliency of the plants network system. The wireless system naturally provides multiple transmission path capability and data redundancy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Thermal Modeling and Limitations for Power Electronics Embedded in Medium-Voltage Cables

As next-generation energy technologies gain traction and power demand increases, the existing electrical infrastructure faces significant stress, prompting innovative solutions to enhance the grid's capacity and lifespan. This work explores the possibility of embedding medium-voltage (MV) power electronics directly inline with the cable, and the resulting thermal challenges. Since the majority of power distribution cables installed in the U.S. are passively cooled, the work focuses primarily on passive cooling, with an emphasis on the limitations of axial heat spreading within the cable. To date, literature on axial spreading of high incident heat loads on cables and cable environments is limited, typically reporting cases with <10 W of incident heat load. This work will explore the considerations, limits, and tradeoffs of cable-embedded heat loads significantly larger than the cable losses. Both external and internal effects are modeled analytically in nondimensional terms via a Biot number analysis, allowing fundamental limits and tradeoffs to be derived. The work culminates in the design and experimental validation of a cable-embedded thermal system capable of passively dissipating 300 W of heat from a coaxial SiC mosfet switch module over a length of 20 cm, thus validating the possibility of MV cable-embedded power electronics from a thermal standpoint.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Harnessing the Hydroelectric Potential of Engineered Drops (Final Technical Report)

The potential for low-head hydropower in the engineered drops in both federal and private irrigation system is well known and significant. The environmental and socio/recreational impacts of harnessing this renewable energy resource in man-made conduits are much less, and often insignificant, compared with comparable hydro-electric potential in natural water features on rivers, lakes, and streams. Yet, few new plants have been commissioned in more than two decades. Over the same time period, low head hydro installations in Germany have more than doubled. The challenge is in finding economical ways to harness the hydro-electric potential in the engineered drops, and efficiently deliver the power to the grid. The objectives of Percheron Power, LLC's (Percheron Power) Project were to design, develop, permit, and operate an innovative low-head hydro-electric generation facility on an existing engineered drop of a large irrigation canal system. The hydro-electric generation facility was designed to employ a new type of turbine and technology, called an Archimedes Hydrodynamic Screw (AHS), to harness the existing potential of the engineered drop. The goal was to demonstrate the new lower cost AHS technology system to federal agencies, irrigation districts and other system owners and to support further development of new small hydropower projects at previously marginal low-head sites in the U.S. The objective of this funding opportunity of the Department of Energy Water Power Technologies Office was to reduce the Levelized Cost of Energy (LCOE) for small hydropower to less than ${$}$0.07/kWh (${$}$70/MWh) to be competitive with existing base-load power sources such as coal-powered power plants.

13 HYDRO ENERGY↗
DOE OSTI2025

Commercialization of a Non-Intrusive Optical (NIO) Technology to Measure Heliostat Optical Errors in Utility-Scale Concentrating Solar Power Plants: Final TCF Report

The drone-based Non-Intrusive Optical (NIO) Technology has been developed at NREL to allow for efficient and automated optical characterization of heliostats in Concentrating Solar Power (CSP) plants. For this project, the technology will be developed into a commercial tool package, including software and user-interface (UI), operations manual, and training and support services. The project team will partner with Tietronix to perform market assessment and stakeholder engagement, develop the tool package and business model, and perform data collection and analysis to demonstrate and refine the capabilities for use at a commercial plant. The team will collaborate with a commercial plant to conduct the data collection operations and provide optical error deliverables. The goal of the project is to advance the commercialization of the technology to a stage where a beta version can be demonstrated at additional commercial plants and developed into a licensable product.

14 SOLAR ENERGY↗
DOE OSTI2024

Using Parameter Sweep in WaterTAP to Analyze New Water Treatment Technologies

We describe a powerful and generalized parameter sweep tool in this report that was originally developed to analyze the performance of existing and novel water treatment models being developed in WaterTAP. Since WaterTAP is built upon IDAES and Pyomo, the parameter sweep tool can be used to systematically explore and debug the behavior of most Pyomo and IDAES numerical models. In order to enable meaningful analyses, the parameter sweep tool has been designed with the following features: 1) Model flexibility: The parameter sweep tool does not enforce any restrictions on the types of models that can be used with it. As long as a Pyomo model can be solved and the parameter is active and mutable, the tool only needs functions that describe how to run the model, the sweep parameters, and the output quantities of interest. 2) Flexible sampling: The parameter sweep tool has inbuilt functions to generate samples from a random distribution or a multidimensional Euclidean space. Furthermore, the users have to ability to supply samples generated from a tool of their choice. 3) Multiple sweep types: A user can choose from one of 3 types of parameter sweeps depending on their needs. 4) Detailed outputs: Outputs generated by the parameter sweep tool can be stored in detailed H5 file or user-friendly CSV files for post processing. 5) Parallel computing: The parameter sweep supports shared and distributed memory parallel computing to enable the use of high performance computers (HPC) for large-scale analyses. 6) Modular: The parameter sweep tool is self-contained and can easily be integrated within an outer-loop analysis or as desired by the user. 7) Ease of use: The tool is well documented and a simple sweep can be easily executed by following the online documentation in a few lines of code. We demonstrate the use of the parameter sweep tool on a simple water treatment system from the WaterTAP repository and show its parallel scaling performance on an Apple laptop and NREL's Eagle HPC. The parameter sweep tool is actively being used with models currently being developed within WaterTAP and we expect its use to grow beyond it to other IDAES and Pyomo models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Project 1: COLLECTS Project and Project 2: M&V for Saputo Cheese Project: Cooperative Research and Development (Final Report)

Project 1: Combined Power's Hyperlight Energy and NLR will collaborate on the DOE Concentrating Optics for Lower Levelized Energy CosTS (COLLECTS) project, DE-FOA-0001268. COLLECTS funding opportunity announcement (FOA) seeks to further concentrated solar power (CSP) system technologies by soliciting disruptive, transformative projects for the concentrating solar collectors in the CSP plant. These innovative projects will seek to surpass the targets set out in the SunShot Vision Study, enabling CSP to be cost-competitive with conventional forms of electric power generation. Projects will target the design and manufacturing of novel solar collectors with the ability to significantly reduce the solar field contribution to the overall levelized cost of energy (LCOE) of the CSP plant, and which have not been previously specifically targeted by CSP FOAs. Project 2: Hyperlight will perform measurement and verification (M&V) of Green House Gases and NLR will evaluate energy consumption reduction.

14 SOLAR ENERGY↗
DOE OSTI2020

Kilopower - Powering the Future of Space Exploration [Poster]

The Kilopower Project was initiated by NASA’s Space Technology Mission Directorate to demonstrate subsystem-level technology readiness of small space fission power in a relevant environment (TRL 5) for space science and human exploration power needs. The Kilopower Project centerpiece is the Kilowatt Reactor Using Stirling Technology (KRUSTY) test, which consists of the development and testing of a ground technology demonstrator of a 1 kWe class fission power system. The technologies to be developed and validated by KRUSTY are extensible to space fission power systems from 1 to 10 kWe, which can enable modular surface fission power systems for human exploration, as well as higher power future potential deep space science missions.

42 ENGINEERING↗
DOE OSTI2023

Artificial Intelligence for a Resilient and Flexible Power Grid

Recent widespread and extreme natural disasters as well as the drive towards clean sustainable energy sources necessitate a transformational operational and technological approaches to improve power grid resilience. Convergence of artificial intelligence (AI), distributed computing, and connectivity technologies enables these new approaches to deliver a sustainable electric grid. In particular, AI-based techniques can enable proactive decision-making by processing massive amounts of data to deliver intelligence at various levels of the system, edge devices to control room. In this chapter, we will explore the potential applications AI-based technology will unlock and challenges to address to achieve a sustainable, flexible power grid.

Omitaomu, Femi↗
DOE OSTI2020

Interoperability Maturity Roadmap Methodology, V1.3

The Interoperability Roadmap Methodology document supports the U.S. Department of Energy (DOE) Grid Modernization Laboratory Consortium (GMLC) Interoperability Project’s efforts to advance interoperability as an essential component for the successful and more seamless integration of intelligent, communicating technologies into the electric power system. This proposed methodology supports the strategic approach to advance interoperability described in the GMLC Interoperability Project’s Interoperability Strategic Vision: Enabling an Interactive Grid. That document proposes engaging an ecosystem of businesses interested in integrating smart technology with the electric power system to develop an interoperability roadmap using a methodical approach. This roadmap methodology is to be applied to technology integration ecosystems (e.g., electric vehicles, photovoltaic inverters, or automated buildings), using tools that measure the state of interoperability today, to identify the gaps and challenges that can be overcome to improve interoperability, and thereby, simplify the integration process.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

An Integrated Framework for Risk Assessment of High Safety Significant Safety-related Digital Instrumentation and Control Systems in Nuclear Power Plants: Methodology and Demonstration

This report documents the activities performed by Idaho National Laboratory (INL) during Fiscal Year (FY) 2022 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk Informed Systems Analysis (RISA) Pathway, digital instrumentation and control (DI&C) risk assessment project. In FY 2019, the RISA Pathway initiated a project to develop a risk assessment strategy for delivering a technical basis to support effective and secure DI&C technologies for digital upgrades/designs. A framework was proposed for this strategy, which aims to (1) provide a best-estimate, risk-informed capability to quantitatively and accurately estimate the risk impact of plant modernization, considering the introduction of high safety-significant safety-related (HSSSR) DI&C systems, (2) support and supplement existing risk-informed DI&C design guides by providing quantitative risk information and evidence, (3) offer a capability of design architecture evaluation of various DI&C systems, (4) assure the long-term safety and reliability of HSSSR DI&C systems, and (5) reduce uncertainty in costs and support integration of DI&C systems in the plant. To achieve these technical goals, the framework provides a means to address relevant technical issues by: (1) defining a risk-informed analysis process for DI&C upgrade, that integrates hazard analysis, reliability analysis, and consequence analysis, (2) applying risk-informed tools to address common cause failures (CCFs) and quantify corresponding failure probabilities for DI&C technologies, particularly software CCFs, (3) evaluating the impact of digital failures at the component level, system level, and plant level, and (4) providing insights and suggestions on designs to manage the risks, thus to support the development and deployment of advanced DI&C technologies on nuclear power plant (NPPs).

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗