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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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We were given a charge to assess the necessity for new or upgraded facilities to ensure the Office of Science (SC) remains at the forefront of scientific discovery. This effort included evaluating five specific ASCR facilities for their potential to contribute to this goal and to rate the readiness for construction of each.
This guide provides introductory information on how to get started in using the web-based Weatherization Assistant audit tool and running the National Energy Audit Tool, Manufactured Home Energy Audit, Multifamily Tool for Energy Audits, and Health and Safety Audit. For new users, this guideline also outlines how you can create a client and start an audit for that client. The Weatherization Assistant is a family of advanced audit tools designed specifically to help states and local weatherization agencies implement the US Department of Energy (DOE) Weatherization Assistance Program. The Weatherization Assistant is developed and maintained by DOE’s Oak Ridge National Laboratory (ORNL). It applies engineering and economic calculations to assist states and agencies in selecting energy-efficient retrofit measures that meet government criteria for cost effectiveness and that can be installed in homes of low-income families enrolled in the program. The Weatherization Assistant can be used to select and rank measures for individual houses, or to establish a priority list of weatherization measures for nearly identical housing types.
Visual inspections by US Customs and Border Protection agriculture specialists have identified approximately 20,000 regulated, quarantined pests each year in agricultural products entering the United States. Most of these pests identified in the Agriculture Quarantine and Inspection (AQI) program are insects. Many pathogens are difficult to detect in agricultural products, particularly in early stages of infection. New technologies can help to detect plant pathogens and the diseases that they cause. This technology assessment was performed for the US Department of Homeland Security Science and Technology Directorate (DHS S&T) through the Food, Agriculture, and Veterinary Defense (FAV-D) program to identify emerging technologies that could address this hard problem. These emerging technologies differ in their diagnostic sensitivities and specificities, as well as in their measurement time and training requirements. New instruments that detect volatile organic compounds characteristic of plant disease or pathogens could provide a less invasive inspection method. Dogs, which can successfully detect many concealed agricultural products, have also been trained to detect some plant pests and pathogens. Simple immunological tests offer sensitive and specific detection of many pathogens at the point of use. Advanced imaging methods that use AI to sort fruits and vegetables and recognize anomalies at high speeds could be used in cooperation with exporters to improve food quality and reduce pests. Advances in nucleic acid–based detection methods that have become gold standards for confirmatory diagnostics are now making those methods available for faster, point-of-use detection. These new methods should be developed in the context of AQI operational requirements, which apply risk-based sampling protocols to protect agriculture and facilitate commerce and passenger transit.
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DOE’s PV Lifetime project was initiated in 2016 with the goal of accurately characterizing the early-life evolution of photovoltaic (PV) field performance. Different PV cell and module technologies result in different initial degradation rates due to effects like light-induced degradation (LID) and light & elevated temperature-induced degradation (LeTID). To accurately characterize the initial field degradation of maximum power (Pmp) requires the use of high-accuracy indoor IV curve measurements at standard test conditions. Therefore, PV modules involved in this study are removed from the field once or twice per year and brought indoors for measurement under constant temperature and irradiance conditions.
This project undertook the first systematic and comprehensive collection of Floating Photovoltaic (FPV) related techno-ecological data across diverse geographic regions of the United States. It examined FPV performance, assessed potential environmental risks and benefits, and provided data to support the development of research protocols for better understanding the impacts of FPV. As part of this process, we conducted a detailed study of four existing FPV sites and three land-based PV (LPV) sites in Florida and California.
Cables are initially qualified for nuclear power plant use for 40 years. As plants extend their operating license to 60 and 80 years, continued use of these cables must shift to a performance-based approach since it is cost prohibitive to completely replace cables that are likely still capable of performing their design function. A variety of cable tests are available and are commonly applied during outages when the cables can be taken out of service. Frequency domain reflectometry (FDR) is one of these test methods that is being more broadly accepted and used because it not only detects anomalies along the cable with a low-voltage signal that does not stress the cable insulation, but the technique also locates the anomalies. This supports follow-up local inspection and local repair or partial replacement of a damaged cable segment. Currently, FDR testing is only applied to cables that are taken out of service since the test instrument would be damaged by operational voltages.
The PIP-II Accelerator is an 800 MeV superconducting Linac in the injection chain of the Fermilab accelerator complex. The LLRF systems for the 125 cavities which include a few normal conducting cavities in the warm front-end section, use a variety of LLRF hardware components and sub-systems that are part of the timing and synchronization system. This includes a master oscillator and phase averaging reference line, a beam pattern generator to enable beam transfer between non-harmonic RF systems and beam loading compensation systems synchronized to a start of beam trigger. The timing signals are based on a 650 MHz clock with manchester encoded event information and data provided over optical fiber. The timing and synchronization systems and their performance parameters will be described here.
Recently, a new graph Laplacian, called the inner product Laplacian, was introduced which generalizes many existing Laplacians, including the normalized and combinatorial Laplacian and their weighted variants. The key observation behind the inner product Laplacian is that by defining appropriate inner product spaces on the vertices and edges, the standard Laplacians can be recovered as Hodge Laplacians over the simplicial complex formed by the edges and vertices. These inner product spaces form a natural way to incorporate non-combinatorial information into the definition of a domain-specific Laplacian. In particular, in contrast to current domain-specific weighting schemes which rely solely on edge weights, information regarding the similarity of non-adjacent vertices and arbitrary pairs of edges can be effectively incorporated into the Laplacian. In order to illustrate this approach we consider the problem of calculating the potential energy of an atomistic configuration using Graph Neural Networks. In comparison with start-of-the-art approaches, such as SchNet, our approach replaces a learned (via auto-encoder) representation of the atom types with an inner product space on atoms based on scientific knowledge (e.g., electronegativity). We will illustrate how this approach captures key chemical properties of the molecules and compare the energy calculations with state-of-the-art neural network approaches. However, to compute the resulting Laplacian involves a mixture of sparse and dense matrix computation and yields a dense matrix as the basis for the graph convolution. This dense convolutional kernel necessitates moving away from the standard message passing framework for graph neural networks and increases the computational cost of applying the kernel. In order to mitigate these costs we investigate means of leveraging the mixed sparse and dense computations to reduce the overall computational cost and how these approaches can be automatically transferred to energy efficient hardware (e.g., field programmable gate arrays (FPGAs)).
This document is presented as the Site Sustainability Plan (SSP) for Lawrence Livermore National Laboratory (LLNL), consistent with the instructions provided by the Department of Energy (DOE) received in August 2024 as a deliverable for DOE Order 436.1A Departmental Sustainability requirement. LLNL is certified in Environmental Management System (EMS) (ISO 14001) and aligns sustainability efforts with the EMS.
Electric vehicles as mobile power (EV-AMP) can allow Texas Army National Guard and others to leverage as few as four electric vehicles (EVs) to provide emergency energy storage for 24 hours by installing bidirectional chargers and associated dark-start equipment. The presence of four or more EVs operating within a regional context creates a more resilient network than a single diesel generator or BESS, and the fleet of vehicles can travel to one of several locations equipped with bidirectional chargers for the service of critical loads.
The objectives of the Wabash Hydrogen Negative Emissions Technology Demonstration Project (Wabash Project) are to develop and design all aspects of the scope, cost, characteristics and investment case of a world class flexible gasification, net negative carbon, hydrogen co-products power plant. The outcome of this undertaking is a complete set of deliverables that has been produced by a preeminent team of engineers, constructors, operators, and developers, building upon previous technology, utilizing cutting edge technology, and thoroughly defining all aspects of this fully integrated 21st Century Powerplant. The Wabash Project encapsulates several cross-cutting initiatives within the US Department of Energy, such as 100% hydrogen powered combustion turbine, geological carbon sequestration, coal with biomass gasification and hydrogen energy storage. The flexible gasifier at the Wabash Valley Resources plant is a slurry-fed, entrained flow, high-temperature, oxygen-blown gasifier that has been proven commercially to operate successfully on various coals and petroleum coke (petcoke). The ability to be fuel flexible and feed various biomass (woody biomass and agriculture residue) and petroleum waste (plastics) was evaluated during BP 1 (BP1). This involved the preparation and testing of feedstocks into slurries to determine what fuels can be fed to the gasifier. By utilizing a flexible oxygen-blown gasifier, the ability to address operational issues common to lower temperature biomass gasification, such as the handling of tars, can be mitigated. The overall goal is to achieve a design capable of carbon-negative emissions while leveraging the substantial investments made and operating experience already gained at the Wabash site.
This report outlines the technical assistance provided to Floyd County Fiscal Court, Kentucky, and Vision Granted through the U.S. Department of Energy Clean Energy to Communities Expert Match Program. Floyd County, designated as “distressed” and “disadvantaged,” faces significant economic challenges, including limited job prospects, high energy costs, and youth “brain drain.” This technical assistance aims to address these pressing issues by implementing strategies to enhance home energy efficiency and livability while also aligning retrofit efforts with goals for resilience and workforce development. Through targeted guidance, this report aims to empower Floyd County residents and organizations in navigating resources for improving housing conditions, creating workforce opportunities, and enhancing resilience.
The photon strength function of 58 Fe has been extracted using both the Oslo and Shape methods from particle-γ coincidence data measured using the Detector Array for Photons, Protons, and Exotic Residues, which probes nuclei utilizing (d,p) reactions in inverse kinematics. Four particle-γ coincidence matrices, each constructed with different treatments of the γ-ray energies, are explored in order to observe the impact on the resulting nuclear level density and photon strength. The final photon strength function reported is found to agree well with previous Oslo measurements of other iron isotopes. Systematic uncertainties are included, using different model parameters and their reported errors to perform the Oslo method normalization. The model-independent Shape method is explored and the functional form of the photon strength function obtained is in agreement with the Oslo method results. A low-energy enhancement is not reported for 58 Fe in this work given possible subtraction issues originating from strongly populated states.
Solid oxide electrolysis cell (SOEC) is a promising technology for high-efficiency energy conversion, enabling the production of hydrogen, syngas, synthetic fuels, and various commodity chemicals. Unlike traditional thermochemical processes, SOECs operate at elevated temperatures (600-850°C), benefiting from favorable thermodynamics and reaction kinetics. This makes them highly energy efficient compared to alkaline or polymer electrolyte membrane (PEM) electrolysis technologies. However, despite these advantages, SOECs face significant challenges related to performance degradation over time. A primary issue is the degradation of the oxygen electrode due to strontium (Sr) segregation and impurity poisoning from chromium (Cr) and sulfur (S). This is because the pathway to deposition of Cr and S include the reaction of Cr and S with the segregated SrO at the surface. Sr segregation leads to the formation of insulating compounds such as SrCrO4 and SrSO4, which block active sites, reduce oxygen exchange rates, and compromise the electrode's electrochemical stability. The degradation mechanisms involve complex interactions between the electrode material's surface chemistry, microstructure, and the operating environment. Sr segregation is particularly problematic because it facilitates the deposition of Cr and S impurities, exacerbating performance losses. Addressing these issues is critical to enhancing the durability and economic viability of SOEC technology. The primary goal of this project is to improve the durability and performance of SOECs by controlling the surface composition of the oxygen electrode. This is achieved by suppressing Sr segregation, thereby mitigating impurity poisoning pathways. The project aims to enhance the oxygen exchange rate, improve cell stability, and extend the operational lifespan of SOECs without necessitating major changes to electrode chemistry or stack components.
The calculation of the spectrum of antineutrinos ( $\overline{V}$ e ) from a reactor is a complicated problem requiring several nuclear data and physics inputs. Many of these have been investigated thoroughly to improve calculations and properly account for uncertainties. One input which has heretofore escaped consideration is the fission yield distribution between ground and isomeric states. In this work, we explore the effect of incorporating newly evaluated isomeric yield ratios (IYR) for 43 fission products into summation calculations and identify the disproportionate importance of certain isotopes, particularly at higher energies. Our analysis indicates that updated IYRs contribute to a significant increase in the $\overline{V}$ e spectrum around and above 7 MeV, with increases of more than 50% at higher energies. Through a detailed sensitivity study, we highlight a number of isotopes for which the IYR has a substantial effect on the $\overline{V}$ e spectrum. This work stresses the critical role of isomeric yields in calculations of reactor $\overline{V}$ e spectra and points to the necessity for their accurate experimental determination, especially for key fission products, in order to refine our understanding and address the observed anomalies between measured and calculated $\overline{V}$ e spectra.
The CSP Systems Analysis project estimates the current market cost of CSP subsystems and technologies for use by the DOE Program and within NREL analysis tools. The project addresses upgrades to NREL's System Advisor Model (SAM) related to CSP, as well as development of new modules within SAM to expand the types of CSP systems that can be simulated and new tools for evaluating CSP subsystem performance or optimizing CSP system layouts, for example, SolarPILOT and SolTrace. The project evaluates the potential cost and performance of new CSP-relevant technologies and generally includes assessment of CSP technologies in support of the DOE subprogram. A primary goal of the CSP System Analysis project is to provide timely and accurate cost data to the DOE to assess the current state of CSP technologies as well as predict performance and cost for pre-commercial and emerging technologies that may impact the industry. Prior work in this task has produced technology cost reports and roadmaps for DOE and highlighted promising research paths that could reduce overall CSP cost, such as the supercritical CO2 power cycle and molten-salt trough systems. CSP Systems Analysis produces modeling tools to evaluate the performance of CSP systems, subsystems, or components, and journal articles, conference papers, technical reports and databases to disseminate information to the CSP industry. CSP technology costs are estimated and tracked using these tools as well as analysis of literature and industry sources. The CSP modeling tools and NREL analysis results are used by researchers; government, financial, and industry analysts; and other CSP stakeholders. The purpose of this final technical report is to summarize the key accomplishments of the past three years of this project. The project was divided into seven separate tasks, and in what follows, we describe the background, objectives, key accomplishments, and path forward for each task within the project, with one section of this report summarizing each task.
In vacuum applications, the thermal decomposition of LiOH corrosion on LiH causes undesirable hydrogen outgassing. The quantity of outgassing is dependent on the thermal stability of the corrosion layer, which depends on sample treatment. We have measured the decomposition of LiOH on as-polished LiH and on previously vacuum-baked LiH (i.e., Li 2 O-covered LiH) which both experienced moisture re-exposure.