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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

PMU Data Quality and Sensor Health Monitoring

Phasor Measurement Units (PMUs) play a critical role in the evolution of the electric power industry by providing high-precision, real-time monitoring of essential power system metrics. However, effectively detecting abnormalities and critical events from PMU data is a complex task, complicated by intricate temporal patterns, a scarcity of labeled data for training algo- rithms, and constraints on online computational power. In this study, we apply TranAD, an innovative algorithm that combines transformer architectures with the refinement of adversarial learning, to both synthetic and real-world PMU datasets for developing a data quality and sensor online health monitoring platform for utilities. Our findings reveal that TranAD not only provides efficient detection and localization but also enhances the detail with which abnormalities are detected, marking a a significant step forward in the field of clean data acquisition processes for power system monitoring

deep neural network, machine learning (ML)↗
DOE OSTI2021

A Cyber Threat Mitigation Approach For Wide Area Control of SVCs using Stability Monitoring

We propose a stability monitoring approach for the mitigation of cyber threats directed at the wide area control (WAC) system used for coordinated control of Flexible AC Transmission Systems (FACTS) used for power oscillation damping (POD) of active power flow on inter-area tie lines. The approach involves monitoring the modes of the active power oscillation on an inter-area tie line using the Matrix Pencil (MP) method. We use the stability characteristics of the observed modes as a proxy for the presence of destabilizing cyber threats. We monitor the system modes to determine whether any destabilizing modes appear after the WAC system engages to control the POD. If the WAC signal exacerbates the POD performance, the FACTS falls back to POD using local measurements. The proposed approach does not require an expansive system-wide view of the network. We simulate replay, control integrity, and timing attacks for a test system and present results that demonstrate the performance of the SM approach for mitigation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Bridging the Gap: User-Centric Energy Monitoring for Policy-Driven Application Optimization in HPC Data Centers

Application energy optimization in HPC data centers face two critical gaps. Systematic methodologies that connect data center policies to application decisions and accessible monitoring tools that enable data-driven optimization. We address both gaps through two complementary pillars. First, we present a methodology based on extended weighted Energy Delay Product (EDP) to translate data center operational priorities and integrate energy considerations into the energy optimization workflow which starts from continuous monitoring through targeted optimization. Second, we present a user-space monitoring tool, Omnistat, that enables this methodology by providing developers with direct access to actionable energy telemetry. Through deployment on the Frontier supercomputer and case studies exploring performance-energy trade-offs, we show how these pillars help energy as an integral optimization target for developers as active participants in data center efficiency.

Shin, Woong [ORNL] (ORCID:0000000172077814)↗
DOE OSTI2022

Lab-on-a-Fish Monitoring Software V1.0

This is the original monitoring software for processing and displaying data for Lab-on-a-Fish. Lab-on-a-Fish simultaneously evaluates and monitors the health, behavior, and environment of fish or small aquatic species. The sensor is a miniaturized underwater monitoring system that measures animal behavior (acceleration and gyration); physiology (electrocardiogram and electromyogram); and environmental parameters (temperature, pressure, and magnetic sensor).

Deng, Daniel↗
DOE OSTI2021

DETECTING FIRE WITH MACHINE LEARNING-ENABLED VISUAL MONITORING FOR NUCLEAR POWER PLANT ENVIRONMENTS

Nuclear power plants are experiencing significant cost challenges to remain competitive with other energy-generation utilities. Unlike other industries, the cost of operation and maintenance activities is mostly attributed to workforce costs. To mitigate this, nuclear power plant stakeholders are increasingly interested in the development and deployment of machine learning methods to potentially automate or augment manually intensive tasks to reduce costs, especially for monitoring activities. One monitoring function that is visually demanding and that can occur frequently to meet the requirements of a fire protection program is visually monitoring an area for fire occurrence. Currently, fire watch activities consist of a worker physically stationed at a given location with the sole responsibility of observing a given area to ensure a fire is detected and mitigated promptly. This effort focused on the development and evaluation of a suitable deep convolutional neural network to classify individual video frames at a sub-second frequency for the occurrence of “fire” and “no fire” in varying industrial environments similar to nuclear power plants. It is believed that a trained neural network model could be integrated with existing facility video surveillance camera feeds to generate alerts when fire inferences occur in individual frames captured at sub-second temporal resolutions. Extensive effort was dedicated to identifying and curating suitable imagery training data representing varying environments and scene settings with and without flame features to maximize generalization in nuclear power plant environments. The data collection effort resulted in the aggregation of a large, labeled image library exceeding 12,000 images to support model training for diverse industrial environments. A deep neural network model incorporating parallel multi-scale capabilities was developed and trained to support accurate image-based detection of flame incidents of varying sizes and spectral feature properties within heterogeneous scenes. Analysis results show that the trained model can achieve high inference accuracy despite heterogeneous scene environments and components. Testing accuracy exceeded 95.0 percent with very low false positive and false negative inferences.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

A Wrapper to Use a Machine-Learning-Based Algorithm for Earthquake Monitoring

Seismology is one of the main sciences used to monitor volcanic activity worldwide. Fast, efficient, and accurate seismicity detectors are crucial to assess the activity level of a volcano in near–real time and to issue timely warnings. Traditional real–time seismic processing software uses phase onset pickers followed by a phase association algorithm to declare an event and estimate its location. The pickers typically do not identify whether the detected phase is a P or S arrival, which can have a negative impact on hypocentral location quality and complicates phase association. We implemented the deep–neural–network–based method PhaseNet to identify in real time P and S seismic waves on data from one– and three–component seismometers. We tuned the Earthworm binder_ew associator module to use the phase identification from PhaseNet to detect and locate the events, which we archive in a SeisComP3 database. We assessed the performance of the algorithm by comparing the results with existing catalogs built to monitor seismic and volcanic activity in Mayotte and the Lesser Antilles region. Our algorithm, which we refer to as PhaseWorm, showed promising results in both contexts and clearly outperformed the previous automatic method implemented in Mayotte. As a result, this innovative real–time processing system is now operational for seismicity monitoring in Mayotte and Martinique.

58 GEOSCIENCES↗
DOE OSTI2025

Distributed Acoustic Sensing for Whale Vocalization Monitoring: A Vertical Deployment Field Test

Abstract There is growing interest in floating offshore wind turbine (FOWT) technology, where turbines are installed on floating structures anchored to the seabed, allowing wind energy development in areas unsuitable for traditional fixed-platform turbines. Responsible development requires monitoring the impact of FOWTs on marine wildlife, such as whales, throughout the operational lifecycle of the turbines. Distributed acoustic sensing (DAS)—a technology that transforms fiber-optic cables into vibration sensor arrays—has been demonstrated for acoustic monitoring of whales using seafloor telecommunications cables. However, no studies have yet evaluated DAS performance in dynamic, engineered environments, such as floating platforms or moving vessels with complex, dynamic strain loads, despite their relevance to FOWT settings. This study addresses that gap by deploying DAS aboard a boat in Monterey Bay, California, where a fiber-optic cable was lowered using a weighted and suspended mooring line, enabling vertical deployment. Humpback whale vocalizations were captured and identified in the DAS data, noise sources were identified, and DAS data were compared to audio captured by a standalone hydrophone attached to the mooring line and a nearby hydrophone on a cabled observatory. This study is unique in: (1) deploying DAS in a vertical deployment mode, where noise from turbulence, cable vibrations, and other sources posed additional challenges compared to seafloor DAS applications; (2) demonstrating DAS in a dynamic, nonstationary setup, which is uncommon for DAS interrogators typically used in more stable environments; and (3) leveraging looped sections of the cable to reduce the noise floor and mitigate the effects of excessive cable vibrations and strain. This research demonstrates DAS’s ability to capture whale vocalizations in challenging environments, highlighting its potential to enhance underwater acoustic monitoring, particularly in the context of renewable energy development in offshore environments.

Saw, Jaewon↗
DOE OSTI2025

Fiber-Optic Sensing for Earthquake Hazards Research, Monitoring, and Early Warning

The use of fiber‐optic sensing systems in seismology has exploded in the past decade. Despite an ever‐growing library of ground‐breaking studies, questions remain about the potential of fiber‐optic sensing technologies as tools for advancing if not revolutionizing earthquake‐hazards‐related research, monitoring, and early warning systems. A working group convened to explore these topics; we comprehensively examined the application of fiber optics in various aspects of earthquake hazards, encompassing earthquake source processes, crustal imaging, data archiving, and technological challenges. There is great potential for fiber‐optic systems to advance earthquake monitoring and understanding, but to fully unlock their capabilities requires continued progress in key areas of research and development, including instrument testing and validation, increased dynamic range for applications focused on larger earthquakes, and continued improvement in subsurface and source imaging methods. A key current stumbling block results from the lack of clear data archiving requirements, and we propose an initial strategy that balances data volume requirements with preserving key data for a broad range of future studies. In addition, we demonstrate the potential for fiber‐optic sensing to impact monitoring efforts by documenting the data completeness in a number of long‐term experiments. Finally, we outline the features of a instrument testing facility that would enable progress toward reliable and standardized distributed acoustic sensing data. Overcoming these current obstacles would facilitate progress in fiber‐optic sensing and unlock its potential application to a broad range of earthquake hazard problems.

58 GEOSCIENCES↗
DOE OSTI2022

A Wide Dynamic-Range Halo Monitor for 8 GeV Proton Beams at FNAL

Eliminating harmful beam halos is the most important technique for high-intensity proton accelerators. Therefore, beam halo diagnosis is indispensable and becomes more and more important. At J-PARC, a wide dynamic range monitor was installed in the beam transport line in 2012. The device is a two-dimensional beam profile monitor [*, **], and it has a dynamic range of approximately six digits of magnitude by using Optical Transition Radiation and fluorescence screens. The FNAL accelerator complex has been upgrading through increased beam intensity and beam quality. A new beam halo diagnostic device is required in the beam transport line between the booster and recycler. It will be manufactured in a collaboration between J-PARC and FNAL as a part of the U.S.-Japan Science and Technology Cooperation Program in High Energy Physics. We are redesigning the monitor to satisfy FNAL specifications for beam energy, intensity, and size. The equipment will be manufactured at J-PARC and then shipped to FNAL in 2024. In this report, the design of the device will be described.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Hadron Monitor Calibration System for NuMI

NuMI (Neutrinos at Main Injector) beamline at Fermi National Accelerator Laboratory provides neutrinos to various neutrino experiments. The hadron monitor consisting of a 5 by 5 array of ionization chambers is part of the diagnostics for the beamline. In order to calibrate the hadron monitor, a gamma source is needed. We present the status and progress of the development of the calibration system for the hadron monitor. The system based on Raspberry Pi controlled CNC system, motors, and position sensors would allow us to place the gamma source precisely to calibrate the signal gain of individual pixels. The ultimate outcome of the study is a prototype of the calibration system.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

SRS Composite Analysis Monitoring Plan (FY2019 Model Validation)

Using a projected end-state date of 2065 (SRNS 2015b), the Savannah River Site (SRS) Composite Analysis (CA) modeling for each facility and waste site began on the inventory year assigned to it so that source depletion and radionuclide transport out of the system could be appropriately captured. Some SRS waste sites that have already achieved their end states (i.e. end-state inventories and end-state configuration) are currently contributing to the potential off-site public dose through source release, groundwater transport, discharge to on-site surface streams, and stream transport to the CA point of assessments (POAs). The inventory year assigned to these waste sites is 2002 or before. This means that SRS CA results from 2002 and beyond are a reasonable representation for these waste sites that have already achieved their end states and are currently contributing to the potential off-site public dose. The SRS Annual Environmental Report (AER) monitoring can differentiate and separate liquid pathway data allowing the data representing only waste sites at their end state to be produced. Because the SRS CA has projected reasonable end-state impacts from 2002 and beyond, and the AER monitoring can differentiate and separate operating and end-state contributions to annual liquid pathway release, an opportunity exists to use the AER monitoring data to validate the SRS CA model. The CA model validation program uses a graded and systematic approach for taking corrective action, starting with an SRS established administrative dose limit of 15 mrem/yr, below which no action is required. Based on the location of the 2010 SRS CA POAs, the only potential exposure pathway for the public is through surface water. The completion of the FY2019 CA model validation indicates that the SRS CA projected dose, while generally conservative, provides a reasonable representation of the maximum annual doses. These doses are well below the administrative limit; therefore, no additional action is required.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Development of an In-Situ Method for Cable Condition Monitoring in Nuclear Power Plants (SBIR Phase IIB Final Report)

This is the final report of a Small Business Innovation Research (SBIR) project that Analysis and Measurement Services Corporation (AMS) has conducted for the U.S. Department of Energy (DOE) over a seven-and-a-half year period (February 2013 through April 2020 with the awards of Phase I, Phase II and Phase IIB projects). The goal of the project was to design, develop, validate, and demonstrate a technique for in-situ testing of cable insulation polymers that will identify, locate, and provide the degree of aging for cables commonly used in nuclear power plants. During the Phase I project, AMS established that the frequency domain reflectometry (FDR) technique can successfully identify and measure cable insulation degradation that can be trended with aging. In Phase II, AMS performed extensive cable aging studies to correlate FDR measurements with other laboratory condition monitoring techniques and developed aging condition categories to quantify the severity of insulation degradation. In Phase IIB, the project expanded the research to include a wider variety of cable polymers that are used in the commercial nuclear power industry. This work also involved developing acceptance criteria to objectively assess age-related cable degradation while sharing the results of this research with industry, academia, and national laboratories to advance the state of the art in cable aging management technologies. The products developed under this research project provide the nuclear industry with an effective condition monitoring tool to support safe and long-term plant operation. Throughout the project, collaborations and support were received from a variety of industry organizations and individuals including DOE National Laboratories as well as nuclear plant utilities and several other industry experts and cable manufacturers. Contributions from these organizations included the donation of new cables, naturally aged cables, and research collaboration. The validation and commercialization of the products of this project were achieved through opportunities to test and demonstrate the technologies’ capabilities on-site at nuclear power generation and research facilities as well as in the laboratory alongside industry peers and cable testing service companies. The research resulted in a technology that can be used to identify, locate, and quantify age-related degradation in several types of cable polymers. This included developing software and hardware as well as the methodology for using the FDR technique to assess age-related degradation of installed cables. The technology developed under this project can provide nuclear plant management, engineers, and technicians with an in-situ electrical test method to determine if in-service cables need to be replaced, monitored on a periodic basis, or show no evidence of significant age-related degradation that may require action. Near the end of this Phase IIB project, the FDR product was sold to a nuclear power utility in South Korea. This sale of a dedicated aging assessment tool is the beginning of a comprehensive contract with the expectation of twelve (12) units sold to that country. Additionally, the FDR technology has been sold to several industry organizations including a nuclear research institute and the Diablo Canyon nuclear power plant. This technology is also being leased by other nuclear industry service companies for incorporation into aging management programs. The cable testing technology that was developed under this project was also integrated into a comprehensive cable aging assessment service that is being offered to the nuclear industry at the request of U.S. nuclear utilities and is currently part of onsite testing services provided by AMS.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

2018 Long-Term Hydrologic Monitoring Program Report for Rio Blanco, Colorado, Site

This report presents the monitoring data collected by the U.S. Department of Energy (DOE) Office of Legacy Management (LM) at the Rio Blanco, Colorado, Site (Figure 1). The Rio Blanco site was the location of an underground nuclear test during which three nuclear devices were detonated nearly simultaneously in a single borehole in 1973. The test resulted in residual radionuclide contamination at the detonation depths of 5840, 6230, and 6690 feet (ft) (DOE 2015). Monitoring includes the collection of samples from groundwater wells and surface water locations near the site to assess for any potential impacts that may be attributed to the Rio Blanco nuclear test. This report summarizes the laboratory analytical results obtained from the sampling event conducted in 2018. This annual report and previous reports are available on the LM public website at https://www.lm.doe.gov/rio_blanco/Sites.aspx. Data collected during this and previous monitoring events are available on the Geospatial Environmental Mapping System (GEMS) website at https://gems.lm.doe.gov/#site=RBL.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Initial development of an in-situ, passive material surveillance test article for monitoring high temperature reactor structural components

This report describes the development of a family of passively-actuated surveillance test articles, suitable for use in an in-situ reactor test program monitoring the degradation in structural material properties caused by the reactor environment. The test articles apply creep-fatigue-type cyclic load to a test section driven by changes in the reactor coolant temperature converted to mechanical force by differential thermal expansion. The report describes three types of test articles, all of which apply the load to a 316H test section using Alloy 617 as the driver material. The three types of specimens each serve a unique purpose: (1) initial proof-of-concept, (2) validation of the models used to size the specimens to achieve a given strain range, and (3) demonstration that the articles can be miniaturized for use in an actual operating reactor. In addition to the specimen design, fabrication, and testing, this report describes the outline of two types of in-situ monitoring programs, using the test article. Monitoring programs such as these could be a critical component in gaining regulator acceptance for Molten Salt Reactor (MSR) designs using structural materials for which there is little long-term experimental environmental testing or operating experience available for calibrating the component structural design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Selection of Well Locations for Saturated Zone Monitoring at the E-Area Low Level Waste Facility

Savannah River Site (SRS) has adopted a revised approach to performance monitoring of the E- Area Low Level Waste Facility (ELLWF) that adds a saturated zone component to the existing vadose zone monitoring program (Kubilius, 2019). The revised monitoring approach specifies that eight additional water table wells be installed near Slit Trench 1 (ST1) and Engineered Trench 2 (ET2). Six wells will be installed at locations characterized in 2017 and 2018. These include four wells near ET2 (ELF001D, ELF002D, ELF003D, and ELF004D) at locations identified by Kubilius (2019) and two wells north of ST1 (ELF005D and ELF006D) at locations finalized in this report. Additionally, two wells (ELF007D and ELF008D) are to be installed at locations south of ST1 based on characterization work completed in 2020 and documented in this report. This area is near well cluster BGX-2 between the Mixed Waste Management Facility (MWMF) and the ELLWF. The area is upgradient of ELLWF and, contamination in the water table aquifer is sourced from MWMF.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

2020 Results for Avian Monitoring at the Technical Area 36 Minie Site, Technical Area 39 Point 6, and Technical Area 16 Burn Ground at Los Alamos National Laboratory

Los Alamos National Laboratory (LANL) biologists in the Environmental Protection and Compliance Division initiated a multi-year program in 2013 to monitor avifauna (birds) at two open detonation sites and one open burn site on LANL property. In this annual report we compare monitoring results from these efforts among years to monitor trends. The objectives of this study are to 1) determine whether LANL operations impact bird species richness, diversity, or abundance and 2) examine occupancy and nest success of secondary-cavity nesting birds using nestboxes. LANL biologists completed the eighth year of this effort in 2020

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

GMS Station SOH Monitoring Configuration Guide (V.1.2)

The GMS Station State-of-Health (SOH) monitoring capability provides the system controller the ability to view current SOH values and calculated statistics for stations and channels, view trend plots of SOH values, be notified when station SOH status changes, and acknowledge or quiet notifications while the station issues are being investigated. The SOH monitoring capability includes components to acquire CD 1.1 protocol station data, extract SOH information from the raw data packets, process the raw SOH information for display, store the SOH information, and display the SOH information in an interactive display. All these components use system and processing configuration to provide the system controller mission-relevant information about station health. This document is a guide to setting the processing configuration for GMS SOH monitoring.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

GMS Station SOH Monitoring Users Guide (V.1.2)

The Geophysical Monitoring System (GMS) State-of-Health User Interface (SOH UI) is a web-based application that allows a user to view and acknowledge the SOH status of stations in the GMS system. The SOH UI will primarily be used by the System Controller, who monitors and controls the system and external data connections. The System Controller uses the station SOH UIs to monitor, detect, and troubleshoot problems with station data availability and quality.

58 GEOSCIENCES↗