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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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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

CALET Search for Electromagnetic Counterparts of Gravitational Waves during the LIGO/Virgo O3 Run

The CALorimetric Electron Telescope (CALET) on the International Space Station consists of a high-energy cosmic-ray CALorimeter (CAL) and a lower-energy CALET Gamma-ray Burst Monitor (CGBM). CAL is sensitive to electrons up to 20 TeV, cosmic-ray nuclei from Z = 1 through Z ~ 40, and gamma rays over the range 1 GeV–10 TeV. CGBM observes gamma rays from 7 keV to 20 MeV. The combined CAL-CGBM instrument has conducted a search for gamma-ray bursts (GRBs) since 2015 October. We report here on the results of a search for X-ray/gamma-ray counterparts to gravitational-wave events reported during the LIGO/Virgo observing run O3. No events have been detected that pass all acceptance criteria. We describe the components, performance, and triggering algorithms of the CGBM—the two Hard X-ray Monitors consisting of LaBr 3 (Ce) scintillators sensitive to 7 keV–1 MeV gamma rays and a Soft Gamma-ray Monitor BGO scintillator sensitive to 40 keV–20 MeV—and the high-energy CAL consisting of a charge detection module, imaging calorimeter, and the fully active total absorption calorimeter. The analysis procedure is described and upper limits to the time-averaged fluxes are presented.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Time Sequence Machine Learning-Based Data Intrusion Detection for Smart Voltage Source Converter-Enabled Power Grid

Smart inverters of distributed energy resources can enable cloud computing, condition monitoring, result visualization, remote control, and peer-to-peer energy trading in advanced power systems. However, the advent of data injection attacks in the communication architecture can alter measurement characteristics of power grids and have devastating consequences. In this article, we propose a time sequence machine learning-based anomaly detection methodology for detecting cyber intrusion into control signal setpoints and dc voltage signal measurement bias of the voltage source converter (VSC) in wind generators. We first investigated the effects of four types of denial of service, tampering signal, and stealthy-type data intrusion attacks on smart VSCs and overall wind farms. We then proposed a novel time sequence machine learning-based intrusion detection framework that can be implemented to detect different cyberattacks in the VSCs. The performance of the proposed framework has been compared with that of autoencoder and clustering-based intrusion detection framework. The proposed framework was validated by using the IEEE 39 bus power system in the presence of four wind farms in different locations. Using several metrics for intrusion detection performance, we validated the effectiveness of the proposed framework.

42 ENGINEERING↗
DOE OSTI2020

Empowering Energy Efficiency in Existing Big-Box Retail/Grocery Stores (Final Optimization Report)

The Center for Sustainable Energy (CSE), in partnership with the National Renewable Energy Laboratory (NREL), TRC Energy Services, P2S Engineering Inc, Walmart, and five innovative technology providers, are to demonstrate the impact of an integrated suite of pre-commercial energy efficiency (EE) technologies in a large, existing, retail building located within an inland disadvantaged community. Proposed technology packages include three categories of advanced EE solutions: heating, ventilating, air-conditioning, and refrigerating (HVAC/R); lighting; and integrated system and building level controls. The project is designed to impact Walmart’s future store specifications, which can be replicated and deployed in other buildings across California with similar end-use and system characteristics. The following lists the technologies considered for this project: DualCool (HVAC evaporative cooling); Software Motor Company (SMC) (HVAC and refrigeration fan motor); I2S: DC LED lighting; LocBit: building energy management and optimization; Saya: water monitoring.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Boride-based Ceramic Super-high Temperature Thermocouples in Harsh Environments (Final Scientific/Technical Report)

An electromotive force (emf) can be generated along a temperature gradient between the cold end and hot end of a thermoelectric material, termed the Seebeck effect. Based on the Seebeck effect, metallic alloys have been extensively employed to detect temperatures for centuries, named thermocouples. However, commercially available thermocouple alloys suffer from limitations, such as oxidation, chemical degradation, and poor long-term stability under high-temperature harsh environments. This DOE-funded project aimed to develop high-temperature, chemically tolerant thermocouples suitable for operation in extreme environments relevant to semiconducting thermoelectric materials. The research focused on boride-based semiconducting thermoelectric compounds as candidates for next-generation thermocouples with enhanced oxidation resistance, chemical stability, and thermal robustness under conditions representative of charcoal-fired electricity facilities. During the funded years, boride materials were synthesized using an arc-plasma technique under ambient air and argon atmospheres, enabling scalable and cost-effective production compared with conventional boride fabrication methods. The synthesized borides were processed into nanostructured powders, followed by consolidation into dense bulk materials using a spark plasma sintering (SPS) bottom-up approach. Comprehensive characterization was performed, including microstructural analysis, electrical transport measurements, and optical and thermal property evaluation. Both p-type and n-type boride electric legs were fabricated and integrated into boride-based thermocouples. The thermal and irradiation stabilities of the boride nanomaterials and bulk thermoelectric materials were systematically evaluated to assess suitability for long-term operation in harsh environments. Additionally, 12 students were broadly hands-on trained spanning the full research workflow, including word processing and technical editing (e.g., LATEX for manuscript and poster preparation), data collection and analysis (using Python and related libraries and hardware interfaces), sample preparation (including arc-plasma synthesis and spark plasma sintering), and advanced characterization techniques (such as X-ray diffraction, UV–vis spectroscopy, electron microscopy, differential thermal analysis (DTA), and Seebeck coefficient measurements, etc). Overall, this project demonstrated the feasibility of boride-based thermoelectric materials as durable high-temperature thermocouples, providing a promising pathway toward robust temperature sensing technologies aligned with DOE energy infrastructure and extreme-environment monitoring needs.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Numerical Modeling of Anisotropic Elastic-Wave Sensitivity Propagation for Optimal Design of Time-Lapse Seismic Surveys

Reliable subsurface time-lapse seismic monitoring is crucial for many geophysical applications, such as enhanced geothermal system characterization, geologic carbon utilization and storage, and conventional and unconventional oil/gas reservoir characterization, etc. In this work, we develop an elastic-wave sensitivity propagation method for optimal design of cost-effective time-lapse seismic surveys considering the fact that most of subsurface geologic layers and fractured reservoirs are anisotropic instead of isotropic. For anisotropic media, we define monitoring criteria using qP- and qS-wave sensitivity energies after decomposing qP- and qS-wave components from the total elastic-wave sensitivity wavefield using a hybrid time- and frequency-domain approach. Geophones should therefore be placed at locations with significant qP- and qS-wave sensitivity energies for cost-effective time-lapse seismic monitoring in an anisotropic geology setting. Our numerical modeling results for a modified anisotropic Hess model demonstrate that, compared with the isotropic case, subsurface anisotropy changes the spatial distributions of elastic-wave sensitivity energies. Consequently, it is necessary to consider subsurface anisotropies when designing the spatial distribution of geophones for cost-effective time-lapse seismic monitoring. This finding suggests that it is essential to use our new anisotropic elastic-wave sensitivity modeling method for optimal design of time-lapse seismic surveys to reliably monitor the changes in subsurface reservoirs, fracture zones or target monitoring regions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Triton Field Trials Changes in Habitat 360-degree Underwater Videos

This dataset contains the underwater 360-degree video files recorded with a Boxfish 360 camera in La Jolla, CA, near a gravity base anchor of the CalWave xWave wave energy converter in December 2021 over three days, at dawn, noon, and dusk. It was generated to test the ability of using this type of camera mounted on an aluminum frame as a video lander to monitor the artificial reef effect of marine energy devices and associated seafloor structures. The Boxfish 360 is made of 3 cameras each recording its own set of videos. The videos are MOV files that can be viewed individually with any video reader but need to be stitched together to create the 360-degree footage. This dataset contains all the raw video files collected at dawn, noon and dusk on 11/30/2021, 12/01/2021 and 12/02/2021, for about 1h each time. This dataset is associated with the journal manuscript below (linked in resources): Hemery, L.G.; Mackereth, K.F.; Gunn, C.M.; Pablo, E.B. Use of a 360-Degree Underwater Camera to Characterize Artificial Reef and Fish Aggregating Effects around Marine Energy Devices. J. Mar. Sci. Eng. 2022, 10, 555. https://doi.org/10.3390/jmse10050555

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Field Insights: Strengthening Digital Assurance Through On-Site Network Monitoring

The accelerating deployment of digital energy infrastructure, ranging from inverter-based resources (IBRs), battery energy storage systems (BESS), to advanced grid control platforms, has brought unprecedented visibility, flexibility, and efficiency to the electric grid. However, this digital transformation also introduces new cybersecurity challenges, particularly in the form of supply chain risks and operational blind spots at the grid edge. Over the past year, the Department of Energy’s Office of Cybersecurity, Energy Security, and Emergency Response (CESER), through its Rapid Risk Assessment initiative, along with the Grid Deployment Office (GDO), through its Technical Assistance for Digital Assurance (TADA) initiative, have supported a series of on-site network engagements led by Idaho National Laboratory (INL). These engagements, conducted in partnership with asset owners across the country, have focused on identifying real-world vulnerabilities and misconfigurations in operational environments, many of which are not detectable through remote assessments or traditional compliance audits. The goal of this report is to distill key findings and lessons learned during network hunt engagements from INL’s fiscal year (FY) 2024 - 2025. It is intended to help asset owners—regardless of their participation in the program—better understand the evolving threat landscape and adopt practical measures to secure their digital energy infrastructure.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Sensors with Intelligent Measurement Platform and Low-cost Equipment (SIMPLE) for Monitoring and Control of Medium Voltage Distribution Systems with High Penetration of Intermittent Distributed Energy Resources

The primary focus of the SIMPLE project was to develop, commission, test and introduce intelligent voltage and current sensor platform with enhanced characteristics (accuracy, bandwidth and harmonic range) and high measurement granularity for medium voltage distribution system monitoring, protection and control. The enhancements incorporated existing (commercially available) sensors and made them suitable for applications such as voltage regulation, frequency support, fault detection and location, distribution system state estimation, power quality measurements and electrical distribution network topology processing. The development of the intelligent sensor platform was driven by the need for high-fidelity monitoring and control of medium voltage distribution feeder to enable higher penetration of renewable resources and microgrid operation.

14 SOLAR ENERGY↗
DOE OSTI2024

EMP, Attachment 2: Data Management Plan

This Data Management Plan (DMP) is an attachment to the Pacific Northwest National Laboratory Environmental Radiological Air Monitoring Plan (EMP). PNNL is a U.S. Department of Energy Office of Science national laboratory. Radioactive effluent monitoring and environmental surveillance for PNNL operations in Washington State are the responsibility of the PNNL Environmental Protection and Regulatory Programs division and are conducted by the Environmental Radiation Task staff. This DMP describes the data management processes for PNNL radioactive air emissions (stack) monitoring and environmental radiological ambient air surveillance activities.

40 CFR 61 Subpart H↗
DOE OSTI2023

Technology Acceptance Workshop Meeting Proceedings, April 20-29, 2022

The Renewable Energy Wildlife Institute and the National Renewable Energy Laboratory convened a virtual workshop facilitated by the Consensus Building Institute in April 2022 to identify recommendations on how to accelerate the rate of research and development, evaluation, and adoption of technologies for monitoring or minimizing wildlife impacts from wind energy. The workshop drew on expertise from stakeholder groups including technology developers, federal agencies, conservation nonprofits, and the wind industry. Over the course of four sessions, participants discussed incentives and barriers to technology development beginning with early field testing and validation, through full-scale experimental deployment, and finally broad-scale acceptance and commercial deployment.

17 WIND ENERGY↗
DOE OSTI2023

Competitiveness Improvement Project (CIP)

Through the Competitiveness Improvement Project (CIP), the U.S. DOE supports small businesses who design and manufacture small or medium wind turbine technology through cost-shared subcontracts awarded via a competitive process. The goals of the CIP are to: improve cost competitiveness with other distributed generation technology through optimized designs and advanced manufacturing processes; increase the number of certified small and medium wind turbine designs across a wide range of sizes; and accelerate deployment of improved, certified distributed wind energy technology. NREL manages the projects through a defined period of performance subcontract, providing technical monitoring and coordinating technical assistance from DOE labs.

advanced manufacturing↗
DOE OSTI2025

High-Power Electric Vehicle Charging Hub Integration Platform (eCHIP): Site Energy Management System Platform Development

A site energy management system is a critical component of future high-power EV charging hubs. It monitors and supervises all inter-hub operations, coordinates grid interactions, and implements energy management strategies and load-sharing controls at various levels and time scales. This report provides a comprehensive high-level overview and guidelines on the essential elements of such energy management systems. These elements primarily focus on the core functions, architecture, and monitoring aspects of site energy management. The core functions define the grid services and operational objectives that a charging hub is expected to provide and achieve. The architectural section investigates the coordination between hub assets, different control schemes, and their potential benefits and drawbacks. Lastly, the report discusses the needs, types, and functionalities of a monitoring and visualization system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Transformer power management controllers and transformer power management methods

Transformer power management controllers and transformer power management methods are described. According to one aspect, a transformer power management controller includes processing circuitry configured to monitor an electrical characteristic of electrical energy which is received from a secondary of a transformer of an electric power system, use the monitored electrical characteristic to determine transformer loading information which is indicative of an amount of power which is being supplied by the secondary of the transformer to a plurality of loads which are coupled with the secondary of the transformer, and use the transformer loading information to adjust an amount of the electrical energy which is supplied by the secondary of the transformer to at least one of the loads which is coupled with the secondary of the transformer.

Pratt, Richard M.↗
DOE OSTI2025

Optimizing ensemble NV − spin properties of fluorescent diamond microparticles by systematic low pressure high temperature annealing

Low pressure high temperature annealing is a means for driving nitrogen and defect diffusion in diamond to reduce internal lattice damage without the need for technically complicated high-pressure cells. Herein, we perform a systematic time (5, 15, and 30 min) and temperature (1200 °C–1800 °C) study of effects of low-pressure high temperature annealing on photoluminescence, spin concentrations, and spin relaxation properties of NV centers in ca. 3 μm synthetic type 1b diamond particles. Annealing in the temperature range of ca. 1400 °C–1700 °C for even 5 min leads to a higher optically detected magnetic resonance contrast as compared to standard annealing at 900 °C for 2 h. Particles annealed at 1700 °C for 5 min exhibit a contrast close to about 13% as compared to about 9% for those annealed at 900 °C for 2 h. A reduction in the zero-field splitting strain parameter from E ≈ 4.5 MHz to ≈ 2.5 MHz and spectral linewidth from Δν ≈ 7 MHz to ≈ 4 MHz are observed even after 5 min annealing at 1700 °C. Improvements in these spectral parameters resulted in a roughly 2-fold reduction in the noise level of temperature monitoring experiment utilizing an ensemble of NV centers in the particles. Annealing in the temperature range of 1600 °C for 15 or 30 min or 1700 °C for 5 min resulted in NV T 1 relaxation times approaching ca. 5 ms typically observed for bulk diamond. Quantitative electron paramagnetic resonance (EPR) allowed for estimations of thermal activation energies of paramagnetic center annihilation. Monitoring the primary defect concentration (P1 and other defects with half integer spins) and utilizing second order kinetic modeling, an activation energy of 3.63 ± 0.28 eV was estimated. Alternatively, using the NV half field EPR signal and first order kinetic modeling, a similar activation energy 3.89 ± 0.29 eV was estimated.

NV centers↗
DOE OSTI2021

Triton Field Trials (TFiT) underwater noise - University of New Hampshire Living Bridge turbine Processed Data

In July 2021, a commercial-off-the-shelf hydrophone was deployed in a free-drifting configuration to measure underwater acoustic emissions and characterize a 25 kW-rated tidal turbine at the University of New Hampshire's Living Bridge Project in Portsmouth, New Hampshire. Sampling methods and analysis were performed in alignment with the recently published IEC 62600-40 Technical Specification for acoustic characterization of marine energy converters. Results from this study indicate acoustic emissions from the turbine were below ambient sound levels and therefore did not have a significant impact on the underwater noise levels of the project site. As a component of Pacific Northwest National Laboratory's Triton Field Trials (TFiT) described in a paper published in a Special Issue of Journal of Marine Energy Science and Engineering, this study provides a valuable use case for the IEC 62600-40 Technical Specification framework and further recommendations for cost-effective technologies and methods for measuring underwater noise at future current energy converter project sites. The paper can be accessed in the link bellow.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Determining Unabated Airborne Radionuclide Emissions Monitoring Requirements Using Inventory-Based Methods

Compliance with the airborne radionuclide emission monitoring requirements in the National Emission Standards for Hazardous Air Pollutants (NESHAP; 40 CFR Part 61, Subpart H) and State requirements in Washington Administrative Code 246–247 and 173-480 were evaluated for Pacific Northwest National Laboratory (PNNL) operations. Additional guidance may be found in the U.S. Department of Energy Handbook, Environmental Radiological Effluent Monitoring and Environmental Surveillance. To meet regulatory requirements, reviews of planned or proposed projects and activities provide the basis for implementing necessary monitoring adjustments or for implementing changes to projects and activities in a timely manner. Potential unabated off-site doses were evaluated for emission locations managed by PNNL and licensed to the Department of Energy. These locations were at facilities in Richland, Washington (i.e., the Hanford Site and PNNL-Richland Campus) and in Sequim, Washington, (PNNL-Sequim Campus, which formerly was known as the Marine Sciences Laboratory). This report describes the inventory-based methods and provides the results for the NESHAP assessment performed in January 2021 for calendar year ending 2020.

40 CFR 61 Subpart H↗
DOE OSTI2020

Effective Missing Value Imputation Methods for Building Monitoring Data

To understand behaviors of natural and man-made events, such as energy consumption of buildings, which accounts for 40% of energy uses in the US, we deploy automated monitoring devices to record periodic observations. However, such experimental and observation data often contains problems and irregularities that have to be cleaned up before analyses. Due to various conditions affecting sensor operations, the communication channels, recording steps, or the recording media, the recorded data might have missing values, errors, or anomalous values. An effective way to clean up these problems is to replace these missing values, errors and anomalous values with expected values, a process generally known as imputation. In this work, we survey commonly used missing value imputation techniques and compare their performance on a set of building monitoring data. To compare the different types of sensor measurements with widely varying characteristics, we use normalized root mean squared error (NRMSE) as the key metric for the effectiveness of the imputation methods. We additionally consider periodicity and run time when considering comparing methods. Through extensive testing, we find that for small gap sizes, up to 8 consecutive missing values, linear interpolation performs the best; for larger gaps stretching up to 48 consecutive missing values, K-nearest neighbors provides the most accurate imputations; for even larger gaps, more computational intensive methods, such as matrix factorization, achieve the smallest NRMSE. Additionally, we observe that these computationally intensive algorithms not only provide accurate imputations for large gaps, but are also more robust across all types of sensors.

Cho, B↗
DOE OSTI2024

Expert and operator perspectives on barriers to energy efficiency in data centers

Abstract It was last estimated in 2016 that data centers (DCs) comprise approximately 2% of total US electricity consumption. However, this estimate is currently being updated to account for the massive increase in computing needs due to streaming, cryptocurrency, and artificial intelligence (AI). To prevent energy consumption that tracks with increasing computing needs, it is imperative we identify energy efficiency strategies and investments beyond the low-hanging fruit solutions. In a two-phased research approach, we ask: What non-technical barriers still impede energy efficiency (EE) practices and investments in the data center sector, and what can be done to overcome these barriers? In particular, we are focused on social and organizational barriers to EE. In Phase I, we performed a literature review and found that technical solutions are abundant in the literature, but fail to address the top-down cultural shifts that need to take place in order to adapt new energy efficiency strategies. In Phase II, reported here, we interviewed 16 data center operators/experts to ground-truth our literature findings. Our interview protocols focus on three aspects of DC decision-making: procurement practices, metrics and monitoring, and perceived barriers to energy efficiency. We find that vendors are the key drivers of procurement decisions, advanced efficiency metrics are facility-specific, and there is convergence in the design of advanced facilities due to the heat density of parallelized infrastructure. Our ultimate goals for our research are to design DC decarbonization policies that target organizational structure, empower individual staff, and foster a supportive external market.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗