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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

Efficient, Color-Stable, and Long-Lived White Organic Light-Emitting Diodes Utilizing Phosphorescent Molecular Aggregates

Highly efficient and stable single-stack hybrid white organic light-emitting diode (WOLED) devices are developed using two emissive layers: one with amber-colored phosphorescent molecular-aggregate emission from the Pd(II) complex, Pd(II) 7-(3-(pyridine-2-yl-κN)phenoxy-κC)(benzo-κC)([c]benzo[4,5]imidazo-κN)[1,2-a][1,5]naphthyridine, Pd3O8-Py5, and the other with blue fluorescence emission. Here, an optimized device structure achieves high color stability under various current densities, an external quantum efficiency (EQE) of 45.5%, a power efficiency of 97.4 Lm W -1 , and an estimated LT 95 (operational time to 95% of the initial luminance) of 50 744 h at an initial luminance of 1000 cd m -2 .

36 MATERIALS SCIENCE↗
DOE OSTI2020

Reactor and fuel cycle performance of light water reactor fuel with 235 U enrichments above 5%

Recent advances in nuclear fuel materials research, particularly on the topic of accident-tolerant fuels, have brought up potential opportunities for expanding the operating envelope of existing light water reactors. As many of the performance improvements offered by these technologies may be most fully realized by increasing fuel enrichment beyond the standard 5% limit, this paper examines the potential reactor performance and fuel cycle performance of low-enriched uranium oxide fueled light water reactors by generically considering pressurized water reactors with 235 U enrichment from 5 to 7%. Advanced cladding, including accident-tolerant cladding, has the potential to increase fuel burnup limits related to hydrogen in the cladding that coincide with those limits associated with end-of-life reactivity. Therefore, higher enrichment will be necessary in order to realize the higher fuel burnups. This work includes evaluation of the fuel cycle length, discharge burnup, reactivity coefficients, and fuel cycle performance, including radioactive waste and environmental impact metrics per unit energy generated. The analysis was performed using the evaluation metrics from the US Department of Energy Office of Nuclear Energy Fuel Cycle Evaluation and Screening Study. The reactor performance and safety analysis show that enrichments between 5 and 7% would have similar fuel temperature and moderator temperature coefficients. However, the soluble boron coefficient would decrease in magnitude, requiring more corrosive boric acid in the coolant or other methods of reactivity control during the fuel cycle. At these higher enrichments the maximum burnup at the rim of the fuel pellet would increase by almost a factor of two, which is expected to impact the formation of high-burnup structure in the fuel and the corresponding thermo-mechanical fuel properties. The fuel cycle performance assessment shows that increasing enrichment reduces the quantity of high-level waste disposed per unit energy generated, but it increases the natural resource requirements normalized to a gigawatt-electricity-per-year basis. Another impact is the slightly higher discharge burnup, resulting in somewhat different activity levels of the spent nuclear fuel and high-level waste radioactivity at 100 and 100,000 years after fuel discharge. The environmental impacts—including land use, water use, carbon emission, and radiological exposure—are of the same magnitude per unit energy generated. Finally, however, the impacts are distributed differently. Less than 5% enrichment has marginally more impact on the back-end of the fuel cycle, and greater than 5% enrichment has marginally more impact on the front-end of the fuel cycle. Ultimately, no neutronic or reactor safety hindrances to employing light water reactor fuel with enrichments greater than 5% are identified; given the achievable reactor performance benefits with advanced fuels, further practical exploration of increased enrichment fuel is recommended.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Performance Analyses of Supercritical Carbon Dioxide-Based Parabolic Trough Collectors with Double-Glazed Receivers

Supercritical carbon dioxide is becoming a hot research topic as a potential heat transfer fluid in parabolic trough concentrators since it enables operating the solar system at high temperatures for a higher quality of energy. However, the corresponding inflated thermal losses necessitate alternative receiver designs. This work examines four double-glazed receivers, with each annular space being evacuated or non-evacuated, in terms of the absorber tube's diameter (53-80 mm) and the diameter ratios of the two glass shells (1.2-2.0). An analytical model is developed and validated for this purpose, and the four designs are further examined using ground-level solar and meteorological measurements. The results demonstrate higher performance in the case of fully evacuating the receiver and using the smallest possible diameters of the three concentric cylinders, where the energy and exergy efficiencies reach 65.3 and 40.3%, respectively. Yet, evacuating only the inner annular space is sufficient to achieve virtually the same performance level. This energy efficiency decreases to 62% in case of increasing the tube diameter to 80 mm. As the operating temperature increases from 423 to 850 K, the specific thermal losses increase by 3.98-4.34 folds, depending on the receiver design. Double glazing the receivers is favorable only at high operating temperatures of sCO2, where the reduction in thermal losses overcomes the drop in optical efficiency. For an inlet sCO2 temperature of 850 K, thermal losses are reduced by 33.64 and 53.92%, compared to evacuated and non-evacuated single-glazed receivers, respectively. Throughout the year, the fully evacuated and fully non-evacuated double-glazed receivers have energy efficiencies of 54.96 and 52.39%, exergy efficiencies of 33.64 and 32.06%, and thermal losses of 348.8 and 402.5 W/m, respectively.

analytical model↗
DOE OSTI2026

Data Center Cybersecurity, Supply Chain Risk Management, and Emerging Regulation Cohort Summary: Takeaways and Action Plans

This report summarizes the outcomes of the Data Center Cohort under the Department of Energy’s Technical Assistance for Digital Assurance (TADA) initiative, aimed at enhancing grid resilience through cybersecurity, supply chain risk management (SCRM), and Cyber-Informed Engineering (CIE). The cohort engaged 17 organizations across utilities, data center operators, vendors, and technology providers in three sessions combining presentations, discussions, and exercises. Key topics included AI-driven load behavior, cybersecurity vulnerabilities in UPS/BESS and cooling systems, governance gaps at utility–data center boundaries, and supply chain integrity. Five cross-cutting themes emerged: interconnection architecture vulnerabilities, fragmented governance, AI-driven stability risks, lack of regulatory frameworks, and long-term supply chain concerns. Actionable recommendations were developed, including implementing DMZ segmentation, formalizing vendor access agreements, designing AI workload limits, and advancing standards through NERC and state-level programs. These strategies aim to strengthen resilience, clarify responsibilities, and ensure secure integration of data centers into the grid.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Compatibility of LaFe13−x−yMnxSiyH1.6 and Eutectic Liquid GaInSn Alloy

The heat transfer rate of magnetocaloric regenerators is a topic of extensive research and the cyclability of these regenerators is critical to the operation of systems with a high coefficient of performance (e.g., potentially >22, significantly higher than typical vapor compression cooling technologies). To enable a high operating frequency that will result in a high specific cooling power, the heat transfer fluid should have high thermal conductivity and lower specific heat, i.e., higher thermal diffusivity. Eutectic metal alloys possess these qualities, such as gallium–indium–tin (Galinstan), whose thermal diffusivity has been found to be approximately an order of magnitude higher than water. For this study, the effects of eutectic liquid Galinstan exposure on the phase stability of LaFe13−x−yMnxSiyH1.6 magnetocaloric powders in an active magnetic regenerator device were investigated. The powders were characterized before and after exposure to Galinstan using X-ray diffraction, in which the phases were determined using the Rietveld refinement technique and X-ray fluorescence. It was found that after Galinstan exposure, hydrogen containing phases were present in the powder, suggesting that the hydrogen was lost from the magnetocaloric phase. The magnetocaloric phase degradation indicates that the powder was incompatible with the Galinstan metal in an environment with moisture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Editorial for Special Issue “Environmentally Sound In Situ Recovery Mining of Uranium”

This Special Issue features seven articles that cover a range of topics pertaining to the environmentally sound in situ recovery mining of uranium (U ISR). The topics include: (1) methods for assessing the potential environmental impacts of future U ISR operations using historical operational records and available geohydrologic, geochemical and climate data in a specific regional setting; (2) laboratory column studies to parameterize a uranium surface complexation model that can be used to predict uranium fate and transport in groundwater; and (3) a field evaluation of both a chemical reductant and a biostimulant to promote reducing geochemical conditions after oxidative mining at a U ISR facility.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

How Wrong Can the Operational AEP Uncertainty Estimate Be When We Ignore the Correlations Between the Uncertainty Components?

Calculations of wind farm annual energy production (AEP) on operational data are essential for a variety of financial transactions during the life of wind plants. The AEP estimate is associated with an uncertainty value, which is calculated by combining contributions connected to on-site measurements, long-term reference measurements, losses, regression, windiness adjustment, and wind resource interannual variability. Although very limited documentation on the topic exists, the conventional approach currently used by the wind energy community to assess the uncertainty connected to the operational AEP estimate assume that the different uncertainty components are uncorrelated and therefore calculates the overall uncertainty with a sum of squares approach. In this analysis, we contrast the traditional technique to estimate the overall AEP uncertainty by ignoring the correlation between its different components with a novel Monte Carlo based approach, which can instead take into account the correlation between different uncertainty categories. We consider monthly operational data from 472 wind farms from the Energy Information Administration (EIA) 923 database to assess the difference between the two approaches. Long-term wind speed data needed for the AEP assessment are taken from three reanalysis products: the Modern-Era Retrospective analysis for Research and Applications v2 (MERRA-2), the European Reanalysis Interim (ERA-interim), and the National Centers for Environmental Prediction v2 (NCEP-2). The results of the Monte Carlo approach show that three pairs of AEP uncertainty components do show a statistically significant correlation: the uncertainty connected with wind resource inter-annual variability is positively correlated with the one related to the windiness correction and negatively correlated with the one due to the regression, and the wind measurement uncertainty is positively correlated with the regression uncertainty. All these correlations, which are found between uncertainty components which are not only part of an operational analysis, but also of a wind resource assessment, are currently ignored in the conventional techniques used as industry standard. We further investigate the causes of these correlations, in terms of common dependencies of different uncertainty components on wind resource variability, number of data points, and quality of the regression between wind speed and energy production data. Next, we quantify the error in the current industry standard technique, in terms of the percentage difference in total uncertainty calculated with the two considered approaches, for all the analyzed wind farms. We find a mean absolute percentage difference of about 6%, with the largest differences being greater than 20%. The data clearly confirm that ignoring the actual correlation between the uncertainty components can lead to large errors in the assessment of the operational AEP uncertainty, and the proposed Monte Carlo approach should be preferred.

Monte Carlo↗
DOE OSTI2024

Cybersecurity Considerations for Emerging Energy Technologies

AI, cloud computing, post-quantum cryptography, zero-trust architectures, microgrids, and virtual power plants. What do these things have in common? They are all emerging technologies in the clean energy space that will be a critical part of grid modernization efforts. As we work towards clean energy and decarbonization targets, these technologies, developed to solve real-world problems, will help us reach goals and achieve new efficiencies as the paradigm of grid operation shifts. However, there are growing concerns about the cybersecurity risks associated with these trending topics as they are used in critical infrastructure applications. This talk will cover gaps, challenges, and opportunities for the secure implementation of grid modernization solutions and novel energy applications of state-of-the-art networking and communications. Proactive risk mitigation strategies, including the application of cyber-informed engineering, will be discussed. Practical applications of these techniques will help provide countermeasures to the impact of cyberattacks on critical infrastructure technologies in a new, digitized grid landscape.

14 SOLAR ENERGY↗
DOE OSTI2024

An Evaluation of The Dynamic Physical Security Risk Assessment Methodology for Fleet-Wide Applications

The requirements for U.S. nuclear power plants to maintain a large onsite physical security force contribute to their high operational costs. The cost of maintaining the current physical security posture is approximately 10% of the overall operation and maintenance budget for commercial nuclear power plants. The goal of the Light Water Reactor Sustainability (LWRS) program’s physical security pathway is to develop tools, methods, and technologies and provide the technical basis for an optimized physical security posture. The conservatisms built into current security postures may be analyzed and minimized to reduce security costs while still ensuring adequate security and operational safety. The research performed at Idaho National Laboratory within LWRS program’s physical security pathway has successfully developed a dynamic force-on-force modeling framework using various computer simulation tools and integrating them with the dynamic assessment Event Modeling Risk Assessment using Linked Diagrams (EMRALD) tool. This integrated process for physical security analysis is named Modeling and Analysis for Safety Security using Dynamic EMRALD Framework (MASS-DEF). This document provides an update on the progress in applying the MASS-DEF process to an operating commercial nuclear power plant as well as additional industry feedback regarding use of the tool for other physical security risk-informed topics. This report is only a summary of the progress and does not contain specific modeling results as those contain sensitive security information. Previous reports described how a user could integrate their plant-specific force-on-force models with the dynamic simulation tool EMRALD, model operator actions, and integrate with probabilistic risk assessment tools, such as CAFTA (Computer Aided Fault Tree Analysis System) or SAPHIRE (Systems Analysis Programs for Hands-on Integrated Reliability Evaluations), and with thermal-hydraulic tools, such as RELAP-5 or MAAP. Previous reports applied various combinations of available simulations codes with EMRALD using generic plant models to demonstrate how to perform the analysis. This report is an update the progress of applying the dynamic computational framework to an actual nuclear facility using their security scenarios and timelines. This report also provides an update to the procedural guidance for the MASS-DEF process and an overview of the generic models available for use by utilities. This report does not contain any plant’s sensitive information and/or safeguards information. This study’s purpose was to verify that the results achieved using generic models are similar to actual plant results and refine our guidance on the use of the framework. This assessment enables further analysis, such as what-if scenarios and staff-reduction evaluation, thereby optimizing physical security at plants.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Process prediction and detection of faults using probabilistic bidirectional recurrent neural networks on real plant data

Attaining Industry 4.0 for manufacturing operations requires advanced monitoring systems and real-time data analytics of plant data, among other topics. We propose a Probabilistic Bidirectional Recurrent Network (PBRN) for industrial process monitoring for the early detection of faults. The model is based on a Gated Recurrent Unit (GRU) neural network that allows the model to retain long-term dependencies between sensor data along a time horizon, hence learning the dynamic behavior of the process. To reduce the false-positive detection rate of the model, we compel the model to learn from a highly noisy sensor reading while outputting noise-free sensor outputs. The performance of the proposed model is compared to other data-driven statistical process monitoring schemes using real plant data from an industrial Air Separations Unit (ASU) containing noisy sensor readings. We show that the model can learn from noisy data without reducing its performance. Using two different fault cases, we demonstrate the model’s ability to carry out early fault detection with average false-positive rates of 2.9% and 4.9% for both fault cases. The missed detection rates are 0.1% and 0.2%, respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Roadmap on commercialization of metal halide perovskite photovoltaics

Perovskite solar cells (PSCs) represent one of the most promising emerging photovoltaic technologies due to their high power conversion efficiency. However, despite the huge progress made not only in terms of the efficiency achieved, but also fundamental understanding of the relevant physics of the devices and issues which affect their efficiency and stability, there are still unresolved problems and obstacles on the path toward commercialization of this promising technology. In this roadmap, we aim to provide a concise and up to date summary of outstanding issues and challenges, and the progress made toward addressing these issues. While the format of this article is not meant to be a comprehensive review of the topic, it provides a collection of the viewpoints of the experts in the field, which covers a broad range of topics related to PSC commercialization, including those relevant for manufacturing (scaling up, different types of devices), operation and stability (various factors), and environmental issues (in particular the use of lead). We hope that the article will provide a useful resource for researchers in the field and that it will facilitate discussions and move forward toward addressing the outstanding challenges in this fast-developing field.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Introduction to the Minitrack on Monitoring, Control, and Protection.

This minitrack is on topics related to the monitoring, control, and protection of electric power systems for real-time operations and short-term operations planning. This year the emphasis has been on recent developments in the area of large-scale dynamic research for power systems and on hybrid and distributed control concepts for decentralized command and control of existing critical energy infrastructures.

Eto, Joseph H↗
DOE OSTI2021

Optimization-Based Formulations for Short-Circuit Studies with Inverter-Interfaced Generation in PowerModelsProtection.jl

Protecting inverter-interfaced microgrids is challenging as conventional time-overcurrent protection becomes unusable due to the lack of fault current. There is a great need for novel protective relaying methods that enable the application of protection coordination on microgrids, thereby allowing for microgrids with larger areas and numbers of loads while not compromising reliable power delivery. Tools for modeling and analyzing such microgrids under fault conditions are necessary in order to help design such protective relaying and operate microgrids in a configuration that can be protected, though there is currently a lack of tools applicable to inverter-interfaced microgrids. This paper introduces the concept of applying an optimization problem formulation to the topic of inverter-interfaced microgrid fault modeling, and discusses how it can be employed both for simulating short-circuits and as a set of constraints for optimal microgrid operation to ensure protective device coordination.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

A review of machine learning in building load prediction

The surge of machine learning in recent years has been empowering engineer modeling in various fields. The decreasing hardware cost, increasing data accessibility, and advances of building automation system (BAS) allow the collection and storage of a significant amount of building operation data. The two facts provide great opportunities of applying machine learning to building energy systems modeling and analysis. There are a great number of research papers on this topic but there lacks a comprehensive and general review to summarize the current development, limitations, gaps and future trend. In this review paper series, machine learning techniques in building energy system modeling and analysis are reviewed under the organization and logic of the machine learning definition by Tom M. Mitchell: a computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E. This paper is the first part of the review paper series, which focuses on building load prediction. First, the applications of building load prediction model (task T) are reviewed. Then, the modeling algorithms improving machine learning performance and accuracy (performance P) are reviewed. At the same time, the literature on the data perspective for modeling (experience E), including data engineering from sensors level to data level, pre-processing, feature extraction and selection, is reviewed. Finally, what is well-studied and what is lacking but with great potential are concluded; the gaps between present and future utilization of machine learning techniques are identified; the future trend and development are also predicted. The target readers of this paper are not only researchers from the building side who can get exposed to cutting edge machine learning tools, but also those from machine learning side who can understand the potential and challenge to apply machine learning in buildings.

Liang, Zhang↗
DOE OSTI2020

Is there a Perfect D and D Plan - 20100

Problems with many Deactivation and Demolition (D and D) projects arise not necessarily from the technical difficulty of the actions required in a given facility, but rather from lack of integration of the stove piped planning efforts; engineering, operations, environmental, radiological, human resources, etc. This paper will cover Polestar Technical Service, Inc. (Polestar) systems engineering approach to D and D planning based on the company's experience over the past 27 years. This systematic, four-pronged approach to planning is applicable to any D and D project and addresses several diverse topics in a cohesive and integrated manner. The four areas to be discussed are project scope, requirements, facility end state, work force and base operations. This approach progresses a facility through the typical DOE life-cycle from operations, through deactivation, into surveillance and maintenance (S and M) and to eventual demolition and site remediation. To achieve a final end state the approach brings together the efforts associated with identifying and managing the right set of requirements, detailing the scope of work, establishing the baseline, redefining the work processes, aligning the workforce resources with the work processes, and maintaining the base operations activities as the project progresses through the various life-cycle stages. Getting these building blocks right provides a solid framework for executing any D and D project. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Operation and Maintenance of PV Systems: Data Science, Analysis, and Standards

This effort improves the effectiveness and reduce uncertainty in O&M cost through four primary objectives/tasks: 1) institutionalize standards for reliability and availability reporting for large PV power plants; 2) bridge systemic O&M knowledge gaps around important topics affecting O&M; 3) characterize systemic failure modes and patterns and accelerate O&M experiential learning cycles using field data; and 4) establish a baseline understanding of UPVS O&M cost drivers. Key results of this effort include publication of IEC standards, published topical papers on O&M topics, training, and characterize field data for climate- and service-related patterns (additional details below). Integrating these results serves to reduce performance risk and facilitate improvement in the way solar projects are operated and maintained. Results are well received and two publications are among the most successful SETO publications at NREL ("Model of Operation and Maintenance Costs for Photovoltaic Systems with over 40,000 downloads and "Best Practices in Operation and Maintenance of PV Systems, 3rd Ed." with over 90,000 downloads).

14 SOLAR ENERGY↗
DOE OSTI2023

Ultrafast Laser Pulse Generation by Mode Locking: MATLAB-Based Demonstrations

Ultrafast laser spectroscopy is a valuable and increasingly accessible technique for studies of rapid chemical reactions. Critical to ultrafast spectroscopy is the concept of mode locking, a technique that enables a fixed phase relationship between laser modes, resulting in laser pulses with very short duration (in the fs or ps range). Despite the increasing importance of ultrafast lasers in chemistry, the introduction of key concepts behind their operation into the undergraduate and graduate chemistry coursework has been limited. To help the incorporation of these topics into chemistry courses, we report here a hands-on activity that helps students develop an intuitive understanding of the factors that impact electromagnetic wave evolution in optical cavities and the process of mode locking. We first provide the theoretical background by introducing cavity modes and contrasting them with well-known propagating electromagnetic waves. We then explore what happens when modes are added and how the relative phase between the modes affects their behavior. In the second section of this report, three teaching modules are provided, along with associated MATLAB codes and animated images, that can be used in the classroom to introduce concepts of cavity modes and mode locking. These teaching modules start by contrasting propagating electromagnetic waves with cavity modes and then illustrate what happens when multiple modes are present in the cavity and how the relative phase between the modes affects the overall electromagnetic field in the cavity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗