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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Service-Based, Segmented, 5G Network-Based Architecture for Securing Distributed Energy Resources: Preprint

As the number of connected devices in the energy grid increase exponentially, so too are the cybersecurity risks. With the development of modern communications standards such as 5G and beyond the extent to which devices will continue to connect will continue to increase exponentially along with the inherent risks. However, 5G also includes features to help address cybersecurity concerns and therefore helping to mitigate many of these risks. This paper proposes a new service-based network architecture implementing network-slicing capabilities for connected systems and devices to improve performance, availability, security, and reliability of the grid devices and services. This paper considers the quality of service requirements and criticality of services needed for securely monitoring, operating, and securing Distributed Energy Resource (DER) devices. From developed use cases, network slicing is implemented based on these requirements and resource allocations. This work then highlights examples of how slicing can help prevent standard existing attack methods such as a denial-of-service or similar attack which limits resource availability and network bandwidth to the service and thus limiting its ability to affect other services by misbehaving. The designed network architecture use case will be further tested on a local virtualized testbed to verify secure operation and availability of services. Using hardware-in-the-loop devices and systems on this local testbed, this fully segmented, secure network may be realized and evaluated. Finally, this paper presents the results of this testing.

5G↗
DOE OSTI2022

A Data Quality-Aware Framework to Reliably Forecast Photovoltaic Generation and Consumer Load for an Improved Resilience of Microgrids

Photovoltaic (PV) power and consumer load forecasting plays a critical role to ensure operational resilience of the electric grid. Most data-driven forecasting algorithms rely heavily on the continuous availability of good quality data for periodic training and validation. When deployed at the grid’s edge, prolonged disruptions to communications during extreme events degrade data quality. Factors such as missing observations, epistemic uncertainties, data drift, and concept drift are manifestations of data quality that impact the generalization of such field-deployed forecasting models. Currently, there exists no mechanism in the literature to dynamically switch between models under varying degrees of data quality as quantified by certain metrics for each factor highlighted above. This paper addresses this shortcoming by conceptually introducing a data qualityaware framework for reliable PV generation and consumer load forecasting. The framework’s design incorporates components of missing values, divergence tests, and continuous monitoring of generalization performance to detect changes in data quality caused by communications disruptions and trigger specific classes of forecasting models grouped under three use cases (UC1- UC3). As a first step towards validating this framework, real data collected from an actual field microgrid system is used to demonstrate the viability of the three use cases. Results show that the performance is the best in UC1 with an unadjusted R-square value of 0.954, followed by 0.939 for UC2 and 0.757 for UC3.

Sundararajan, Aditya↗
DOE OSTI2025

Utility of near‐surface phenology in estimating productivity and evapotranspiration across diverse ecosystems

Abstract Agroecosystems, which include row crops, pasture, and grass and shrub grazing lands, are sensitive to changes in management, weather, and genetics. To better understand how these systems are responding to changes, we need to improve monitoring and modeling carbon and water dynamics. Vegetation Indices (VIs) are commonly used to estimate gross primary productivity (GPP) and evapotranspiration (ET), but these empirical relationships are often location and crop specific. There is a need to evaluate if VIs can be effective and, more general, predictors of ecosystem processes through time and across different agroecosystems. Near‐surface photographic (red‐green‐blue) images from PhenoCam can be used to calculate the VI green chromatic coordinate (G CC ) and offer a pathway to improve understanding of field‐scale relationships between VIs and GPP and ET. We synthesized observations spanning 76 site‐years across 15 agroecosystem sites with PhenoCam G CC and GPP or ET estimates from eddy covariance (EC) to quantify interannual variability (IAV) in the relationship between GPP and ET and G CC across. We uncovered a high degree of variability in the strength and slopes of the G CC ∼ GPP and ET relationships (R 2 = 0.1 ‐ 0.9) within and across production systems. Overall, G CC is a better predictor of GPP than ET (R 2 = 0.64 and 0.54, respectively), performing best in croplands (R 2 = 0.91). Shrub‐dominated systems exhibit the lowest predictive power of G CC for GPP and ET but have less IAV in slope. We propose that PhenoCam estimates of G CC could provide an alternative approach for predictions of ecosystem processes.

Environmental Sciences & Ecology↗
DOE OSTI2021

Recent Thermal and Hydraulic Stimulation Results at Raft River, ID EGS Site

The Raft River geothermal system, located 160 km northwest of Salt Lake City, Utah is the site of a Department of Energy Enhanced Geothermal System (EGS) stimulation demonstration project. The target well RRG-9 ST-1, is roughly 1.6 km (1 mile) south of the power plant. This well has undergone a series of thermal and hydraulic stimulation treatments. Furthermore, the well passes through approximately 1,524 m MD (5,000 ft. MD) of laterally discontinuous Quaternary and Tertiary volcanoclastic and volcanic rocks that unconformably overlie the Precambrian basement. The Elba Quartzite formation located in the Precambrian basement is the target zone for the stimulation program. Fluid injected into the well exits through a fracture zone in the Elba Quartzite at 1,567 m TVD (5,140 ft. TVD). In June 2013 low-rate stimulation began at RRG-9 ST-1 using injection water from the geothermal plant. The average injection rate, temperature, and well head pressure of the low-rate stimulation was 163 Lpm (43 gpm), 34°C, and 1,931kPa (280 psig), respectively. This injection continued through late August of 2013 when wellhead pressures were intentionally increased to approximately 5,516 kPa (800 psig) at approximately 984 Lpm (260 gpm). From September 12 to September 24, 2013 cold well water was injected. The average surface injection temperature was approximately 12°C. On September 25, 2013 injection of the warmer plant water was resumed. This was continued through the rest of 2013 and into 2014. Between April 1, 2014 and April 4, 2014, a higher rate hydraulic stimulation was conducted. Colder water (~10°C) was injected at rates of 20 bpm to 30 bpm (3,178 Lpm to 4,770 Lpm) at wellhead pressures of 5,861 kPa (850 psig) over approximately 24 hours. Microseismic activity was recorded near the Tertiary-Precambrian contact. Subsequently, injection of water from the plant was resumed. As of mid-January, 2015, over 666 million liters (176 million gallons) have been injected into the well. The fate of this water is the subject of ongoing numerical analyses and continuous site monitoring. Various analyses have been implemented to monitor and assess the ongoing stimulation program. Modified Hall plot analysis shows increasing conductivity and/or a decreasing skin factor around the wellbore. Since April, 2014, the injectivity index has increased significantly from 0.28 Lpm/kPa (0.5 gpm/psig) to 0.93 Lpm/kPa (1.7 gpm/psig).

enhanced geothermal system↗
DOE OSTI2024

2024 OES-Environmental 2024 State of the Science Report, Chapter 11: Summary and Path Forward

The 2024 State of the Science report has brought together the most up-to-date information on potential environmental effects of marine renewable energy (MRE) development on marine animals, habitats, and ecosystem processes, as well as social and economic systems, using information that is publicly available as well as expert input. The report has been reviewed by over 56 experts. The reviewers provided in excess of one thousand comments during the drafting of the report that have been addressed in this version. The OES-Environmental country representatives from the 16 participating countries helped to scope the entirety of the report and provided valuable contributions to all chapters. The input from these contributors and reviewers has resulted in the most complete compendium of research and monitoring findings possible. While there is new and exciting research underway that should further illuminate the risks of MRE stressor-receptor interactions in the near future, suppositions and incomplete results from unpublished studies were not included in order to maintain the integrity, and decrease the uncertainty, of the messages in this report

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

Integrating Survival Analysis with Bayesian Statistics to Forecast the Remaining Useful Life of a Centrifugal Pump Conditional to Multiple Fault Types

To improve the viability of nuclear power plants, there is a need to reduce their operational costs. Operational costs account for a significant portion of a plant’s yearly budget, due to their scheduled-based maintenance approach. In order to reduce these costs, proactive methods are required that estimate and forecast the state of a machine in real time to optimize maintenance schedules. In this research, we use Bayesian networks to develop a framework that can forecast the remaining useful life of a centrifugal pump. To do so, we integrate survival analysis with Bayesian statistics to forecast the health of the pump conditional to its current state. We complete our research by successfully using the Bayesian network on a case study. This solution provides an informed probabilistic viewpoint of the pumping system for the purpose of predictive maintenance.

42 ENGINEERING↗
DOE OSTI2024

Vegetation Warming Experiment: Landscape-scale digital camera imagery for vegetation phenology, Utqiagvik (Barrow), Alaska, 2019

Images captured using a StarDot NetCam SC phenocamera looking east from the top of the Barrow Environmental Observatory (BEO) Sled Shed, Utqiagvik, Alaska. The camera was installed to remotely monitor plant phenology and operation of the Brookhaven National Laboratory (BNL) TEST group's ZPW (Zero Power Warming) chambers during the growing season of 2019. Images were captured from early spring (4 April) through to mid fall (30 October). Snowmelt, vegetation growth and senescence, and snow accumulation were captured. Images were uploaded to the BNL FTP server every hour, then from 2019-06-27 to 2019-10-02 images were recorded every 10 minutes, then at hourly intervals until the end of data collection on 2019-10-30. Files were renamed with the date and time of the image. jpg images have been compressed in *.tar.gz format (5.6 GB). Closer fields of view (northeasterly) were also captured using 4 Wingscapes TimelapseCam cameras mounted on a mast on the sled shed. These cameras were operated from 2019-06-23 to 2019-09-25, with images recorded every 30 minutes from 9:00 to 16:30 Alaska daylight time (AKDT, UTC-8). Individual jpg images have been compressed in zip format for each camera and also presented as mp4 timelapse movies.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Anomaly Detection for Online Monitoring of Thermocouple Sensors in the Advanced Test Reactor

This study explores data-driven anomaly detection methods to analyze sensor fail- ures in the Advanced Gas Reactor (AGR) nuclear fuel irradiation experiments. Specifically, we examine failures of thermocouples (TCs), which are critical for mon- itoring and controlling in-reactor temperatures during operation. Failures were pri- marily observed during abrupt power transitions and manifested as sensor drop-outs, drifts, or unexplained behavior. We applied three time-series analysis techniques— rolling mean smoothing, matrix profile, and vector auto-regression (VAR)—to de- tect anomalies in TC data prior to failure events. The rolling mean method effec- tively highlighted deviations aligned with reported failures, while the matrix profile provided partial early warning but sometimes flagged normal fluctuations during power-down periods. VAR shows potential in capturing multivariate dependencies but requires further calibration. A rare case of TC drift was also documented, which did not result in failure, underscoring the challenge of building predictive models with sparse positive examples. Our findings demonstrate that traditional statistical tools can aid anomaly detection but have limited predictive power without richer training data. We propose future directions including synthetic data generation, real- time surrogate modeling, and multi-modal feature integration. This work provides a foundation for applying robust anomaly detection frameworks to mission-critical sensor systems in experimental settings.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Test and Evaluation of Radiofrequency Tamper Indicating Devices for Remote Monitoring of Advanced/Small Modular Reactors

Advanced and small modular reactors (A/SMRs), due to their versatile nature, are likely to be used in remote locations to provide electrical power or other services in regions that are difficult to access or have limited transportation infrastructure. This will result in limited on-site staff, therefore driving A/SMR vendors to consider remote monitoring as a solution to support nuclear security. Maintaining Continuity of Knowledge (CoK) of nuclear material quantities and locations is vital to nuclear security, and remote monitoring of active tamper indicating devices (TIDs) has been well established as a component of International Atomic Energy Agency (IAEA) Safeguards since the early 2000s. Active TIDs, such as radiofrequency TIDs (RFTIDs), immediately alarm upon unauthorized access attempts, promoting timely detection. In contrast, passive TIDs require a surveillance regime and offer delayed detection. Active TIDs deter insiders and enable prompt detection of malicious acts. They can be used on nuclear material containers and controlled entry points like vaults and toolboxes. Therefore, the implementation of RFTIDs into security programs bolsters overall nuclear material control, and provides a visible deterrent, with primary efficacy in mitigating the insider threat and potentially allowing for Security by Design considerations. They are a strong candidate technology for maintaining nuclear security of A/SMRs but need to be evaluated for feasibility and implementation into the wider physical protection system.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Review—Micro-Fuel Cell Principal Biosensors for Monitoring Transdermal Volatile Organic Compounds in Humans

Knowledge of transduction mechanisms in biosensing applications paves the way for ultrasensitive and dynamic detection in living systems. Real-world biosensing applications where ultra-sensitivity and dynamic detection are paramount include monitoring the anesthetic agent concentration during surgery; the slightest variation in concentration can potentially result in a life-threatening overdose or, on the other end of the spectrum, the patient’s awareness during the procedure. We review the benefits and functions of the transcutaneous biosensor device compared with other current technology and discuss the sensor’s capability to accurately measure volatile anesthetic gas concentration in blood using fuel cell technology. We review fundamental concepts of fuel-cell technology for wearable bio-sensing applications. The fuel cell sensor can also continuously monitor other volatile organic compounds making it versatile with numerous potential applications.

42 ENGINEERING↗
DOE OSTI2021

Occupancy-Driven Stochastic Decision Framework for Ranking Commercial Building Loads

For effective integration of building operations into the evolving demand response programs of the power grid, real-time decisions concerning the use of building appliances for grid services must excel on multiple criteria, ranging from the added value to occupants' comfort to the quality of the grid services. In this paper, we present a data-driven stochastic decision-support framework to dynamically rank load control alternatives in a commercial building, addressing the needs of multiple decision criteria (e.g. occupant comfort, grid service quality) under uncertainties in occupancy patterns. We adopt a stochastic multi-criteria decision algorithm recently applied to prioritize residential on/off loads, and extend it to i) consider complex load control decisions (e.g. dimming of lights, changing zone temperature set-points) in a commercial building; and ii) systematically integrate zonal occupancy patterns to better identify short-term (and time-varying) opportunities for grid service participation. We evaluate the performance of the proposed framework for curtailment of air-conditioning, lighting, and plug-loads in a multi-zone commercial office building for a range of design choices. With the help of a prototype system that integrates an interactive \textit{Data Analytics and Visualization} frontend we demonstrate a way for the building operators to monitor and change in real-time the available flexibility in energy consumption and to develop trust in the decision recommendations by interpreting the rationale behind the ranking.

Jain, Milan↗
DOE OSTI2023

Toward Statistical Real-Time Power Fault Detection

We propose statistical fault detection methodology based on high-frequency data streams that are becoming available in modern power grids. Our approach can be treated as an online (sequential) change point monitoring methodology. However, due to the mostly unexplored and very nonstandard structure of high-frequency power grid streaming data, substantial new statistical development is required to make this methodology practically applicable. The paper includes development of scalar detectors based on multichannel data streams, determination of data-driven alarm thresholds and investigation of the performance and robustness of the new tools. Due to a reasonably large database of faults, we can calculate frequencies of false and correct fault signals, and recommend implementations that optimize these empirical success rates.

bolted faults↗
DOE OSTI2022

Energy Management Information Systems Cybersecurity Best Practices

Energy management information systems (EMIS) are a broad and rapidly evolving family of tools that monitor, analyze, and control building energy use and system performance. Critical systems are often integrated with or operate on the same networks as EMIS scope systems, necessitating stable, continuous, and secure communication. When connecting EMIS to building automation and utility control systems, there are also many physical assets that could cause harm to the building and its occupants if a malicious act or human error were introduced. It is imperative to ensure all EMIS scope systems are connected securely to the EMIS and do not open vulnerable pathways to other facility networks and operations. The Federal Energy Management Program (FEMP) promotes best practices for impactful utilization of EMIS at federal facilities. This best practice document is part of a series of fact sheets created to help accelerate the market adoption and use of EMIS in the federal sector. It provides an overview of required EMIS cybersecurity standards for compliance and authority to operate along with additional recommendations.

cybersecurity↗
DOE OSTI2025

Grid Modernization of Cooperatives and Municipal Utilities via Breakthrough System Monitoring, Control and Optimization (CRADA Final Report)

This project aims at developing and demonstrating successful implementation of breakthrough approaches in real-time data visualization as well as real-time distributed DER control and optimization to provide ample benefits to both utilities and end users. The National Renewable Energy Laboratory (NREL), Holy Cross Energy (HCE), National Rural Electric Cooperative Association (NRECA) and Survalent are collaborating to enable Cooperative and Municipal utilities to fully leverage DERs as part of their strategies for providing safe, reliable, and affordable electric services to their customers and help meet DOE Grid modernization goal of achieving at least 10% active devices to provide grid flexibility by 2035. This project will use novel real-time control algorithms and approaches for distributed control recently developed under DOE-funded projects, using the date from the Survalent’s basic SCADA engine, GIS and AMI engines deployed at HCE combined with NRECA’s globally-used MultiSpeak(R) software interoperability specification for seamless and real-time communications between electric utility enterprise software to embrace DER as part of their strategies for providing safe, reliable and affordable electric service to their customers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Event Screening Methods for the Eastern Interconnection Situational Awareness and Monitoring System (ESAMS)

The Eastern Interconnection Situational Awareness and Monitoring System (ESAMS) is a tool developed to explore the applications and advantages of sharing phasor measurement unit (PMU) data among operating entities. An initial conclusion from testing was that detected events required further screening before being reported to ensure that events would be of interest to system operators. The methods described in this report were integrated into ESAMS to meet this need. First, an event is screened for whether the change in voltage angle measurements indicates that the detected disturbance is sufficiently large. Next, an event is classified to determine if it was related to a loss of generation. Finally, a neural network is used to determine if the system’s response to the disturbance is normal or abnormal. These methods were tested with one month of field-measured PMU data. Results indicate that the additional information provided by these additional screening tools will improve selection of events for inclusion in the daily event reports automatically generated by ESAMS.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Multidecadal Biological Monitoring and Abatement Program assessing human impacts on aquatic ecosystems within the Oak Ridge Reservation in eastern Tennessee, USA

Human activities can be powerful drivers of ecosystem change within catchments. While most long-term catchment studies have been conducted at pristine sites, such studies are less common from sites more impacted by human activity. The Oak Ridge National Laboratory's Biological Monitoring and Abatement Program (BMAP) was developed in the mid-1980s to (1) assess compliance with environmental regulations, (2) identify causes of adverse ecological impacts, (3) provide data for human and ecological risk assessments, and (4) evaluate the effectiveness of remedial actions taken to mitigate the impacts of contaminants in soils, groundwater, and surface water by documenting ecological recovery on the Oak Ridge Reservation (ORR), a federally owned 33,476-acre site in eastern Tennessee, USA, managed by the U.S. Department of Energy. The ORR is composed of multiple watersheds containing many small to mid-size streams. BMAP uses an integrated approach for determining stream health; its databases include long-term seasonal records of contaminant concentrations in water and biota, data from aquatic toxicity testing, and surveys of macroinvertebrate and fish assemblages from impacted and reference streams. These long-term data provide valuable records of degradation and recovery in catchment ecosystems. Our objective in this work is to describe our study system and data series in order to increase awareness of the availability of these long-term data to the catchment science community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Bayesian-based response expansion and uncertainty quantification using sparse measurement sets

Systems subjected to dynamic loads often require monitoring of their vibrational response, but limitations on the total number and placement of the measurement sensors can hinder the data-collection process. Here, we present an indirect approach to estimate a system’s full-field dynamic response, including all uninstrumented locations, using response measurements from sensors sparsely located on the system. This approach relies on Bayesian inference that utilizes a system model to estimate the full-field response and quantify the uncertainty in these estimates. By casting the estimation problem in the frequency domain, this approach utilizes the modal frequency response functions as a natural, frequency-dependent weighting scheme for the system mode shapes to perform the expansion. This frequency-dependent weighting scheme enables an accurate expansion, even with highly correlated mode shapes that may arise from spatial aliasing due to the limited number of sensors, provided these correlated modes do not have natural frequencies that are closely spaced. Furthermore, the inherent regularization mechanism that arises in this Bayesian-based procedure enables the utilization of the full set of system mode shapes for the expansion, rather than any reduced subset. This approach can produce estimates when considering a single realization of the measured responses, and with some modification, it can also produce estimates for power spectral density matrices measured from many realizations of the responses from statistically stationary random processes. A simply supported beam provides an initial numerical validation, and a cylindrical test article excited by acoustic loads in a reverberation chamber provides experimental validation.

42 ENGINEERING↗
DOE OSTI2024

Interpreting Forced Oscillation Notifications from ESAMS: General Guidance for Reliability Coordinators

The Eastern Interconnection Situational Awareness Monitoring System (ESAMS) project demonstrated the feasibility of aggregating synchrophasor measurements from across an interconnection, analyzing them, and providing real-time wide-area situational awareness to system operators who may have excellent visibility within their footprint but lack an interconnection-wide view. An application within ESAMS that has garnered industry interest involves detecting forced oscillations visible across multiple areas, identifying the region where the oscillation originated from, quantifying the uncertainty in source localization results, and notifying users in real-time if the detected oscillation amplitudes cross a specified threshold. It is expected that system operators will utilize their internal SCADA/EMS/synchrophasor systems in conjunction with information provided by ESAMS to take effective mitigation actions if forced oscillation notifications are received. This report provides some general guidance on how the ESAMS information can be used for source localization and coordination among multiple reliability coordinators; and also identifies potential enhancements to ESAMS notifications for improved interpretability.

24 POWER TRANSMISSION AND DISTRIBUTION↗