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At least 19 records

Generator Frequency Response Droop Monitoring Tool

Monitoring and analyzing the frequency response performance of power generation units is essential for maintaining reliable and secure power system operation. To address this need, an automation tool has been developed to provide a pipeline for processing historical power plant generation data, including large-scale SCADA archives. The tool performs end-to-end processing, including event detection, frequency response (FR) analysis in accordance with NERC standards, and estimation of speed governor droop characteristics. The tool is designed with a modular architecture, allowing individual components of the workflow to be extended, customized, or deployed independently. In addition, the tool provides an API that enables seamless integration with other production systems and operational analytics platforms.

Etingov, PavelV [Pacific Northwest National Labora↗

Interagency Collaborators Develop and Implement ForWarn, a National, Near Real Time Forest Monitoring Tool

ForWarn is a satellite-based forest monitoring tool that is being used to detect and monitor disturbances to forest conditions and forest health. It has been developed through the synergistic efforts, capabilities and contributions of four federal agencies, including the US Forest Service Eastern Forest and Western Wildland Environmental Threat Assessment Centers, NASA Stennis Space Center (SSC), Department of Energy's (DOE) Oak Ridge National Laboratory (ORNL) and US Geological Survey Earth (USGS) Earth Research Observation System (EROS), as well as university partners, including the University of North Carolina Asheville's National Environmental Modeling and Analysis Center (NEMAC). This multi-organizational partnership is key in producing a unique, path finding near real-time forest monitoring system that is now used by many federal, state and local government end-users. Such a system could not have been produced so effectively by any of these groups on their own. The forests of the United States provide many societal values and benefits, ranging from ecological, economic, cultural, to recreational. Therefore, providing a reliable and dependable forest and other wildland monitoring system is important to ensure the continued health, productivity, sustainability and prudent use of our Nation's forests and forest resources. ForWarn does this by producing current health indicator maps of our nation's forests based on satellite data from NASA's MODIS (Moderate Resolution Imaging Spectroradiometer) sensors. Such a capability can provide noteworthy value, cost savings and significant impact at state and local government levels because at those levels of government, once disturbances are evident and cause negative impacts, a response must be carried out. The observations that a monitoring system like ForWarn provide, can also contribute to a much broader-scale understanding of vegetation disturbances.

Underwood, Lauren↗

Individualized Behavioral Health Monitoring Tool

Behavioral health risks during long-duration space exploration missions are among the most difficult to predict, detect, and mitigate. Given the anticipated extended duration of future missions and their isolated, extreme, and confined environments, there is the possibility that behavior conditions and mental disorders will develop among astronaut crew. Pulsar Informatics, Inc., has developed a health monitoring tool that provides a means to detect and address behavioral disorders and mental conditions at an early stage. The tool integrates all available behavioral measures collected during a mission to identify possible health indicator warning signs within the context of quantitatively tracked mission stressors. It is unobtrusive and requires minimal crew time and effort to train and utilize. The monitoring tool can be deployed in space analog environments for validation testing and ultimate deployment in long-duration space exploration missions.

Mollicone, Daniel↗

GSMS and space views: Advanced spacecraft monitoring tools

The Graphical Spacecraft Monitoring System (GSMS) processes and translates real-time telemetry data from the Gamma Ray Observatory (GRO) spacecraft into high resolution 2-D and 3-D color displays showing the spacecraft's position relative to the Sun, Earth, Moon, and stars, its predicted orbit path, its attitude, instrument field of views, and other items of interest to the GRO Flight Operations Team (FOT). The GSMS development project is described and the approach being undertaken for implementing Space Views, the next version of GSMS, is presented. Space Views is an object-oriented graphical spacecraft monitoring system that will become a standard component of Goddard Space Flight Center's Transportable Payload Operations Control Center (TPOCC).

Carlton, Douglas↗

DejaVu: A Monitoring Tool for First-Order Temporal Logic

Runtime Verification (rv) is aimed at analyzing individual execution traces and temporal behaviors observed from running programs and systems. Its traditional purpose is in detecting the lack of conformance with respect to a formal specification. While very early rv systems were based on specifications given in some form of propositional temporal logic, recent efforts have focused on monitoring so-called parametric specifications over events that carry data. Since a monitor for such specifications has to store observed data, the challenge is to have an efficient representation and manipulation of data. The fundamental problem is that the actual values of the data are not necessarily bounded or provided in advance. In this paper, we describe our monitoring tool, DejaVu, which implements our algorithm [HPU17] for monitoring first-order past linear-time temporal logic over a sequence of events that carry data. We propose the use of Binary Decision Diagrams (bdds) [Bry86] for representing and manipulating sets of observed data since (1) bdds provide highly compact representations, (2) operations over bdds, in particular complementation, are very efficient, and (3) the monitor construction for the propositional case shown in [HR02] naturally extends to bdds. Our experiments show a substantial improvement in performance compared to a related tool.

Ulus, Dogan↗

TEAMER - Field Demonstration of MarineSitu’s Marine Energy Monitoring Tools - CRADA 664 (Abstract)

In order to effectively monitor for marine life around marine energy devices and thus minimize the risk of collision, multiple sensors working in coordination and augmented with around-the-clock automated monitoring algorithms need to be installed in challenging high-energy tidal and wave environments. Such systems are often too expensive for widespread adoption, or lack sufficient sensors or smarts to enable around-the-clock, real-time monitoring without human involvement. MarineSitu has been working to tackle this problem by developing a low-cost, combined sonar and stereo camera sensor array with connected real-time AI-based algorithms for automatically detecting marine life in these marine energy suitable environments. In this TEAMER project with Pacific Northwest National Lab (PNNL), MarineSitu will be testing this novel sensor system for the first time in the high-energy tidal channel environment at PNNL’s Marine and Coastal Research Lab. Throughout this deployment, MarineSitu will be monitoring their system and running analytics on the sensor’s data in real-time. Meanwhile, PNNL Data Scientists and Ocean Engineers, will be evaluating the system’s effectiveness and ease of use both as a tool for plug-and-play environmental monitoring and novel environmental monitoring research. In doing so, the team will improve MarineSitu’s system and software, produce insightful data products, and develop novel visualizations and AI algorithms for combining and analyzing the data produced by systems like MarineSitu’s.

16 TIDAL AND WAVE POWER↗

Improving Coal-Fired Plant Performance Through Integrated Predictive and Condition-Based Monitoring Tools

The project demonstrated the ability to improve boiler performance and reliability through the integrated use of condition-based monitoring (CBM) and predictions of the impacts of coal quality on boiler operations at a full-scale coal-fired power plant. The advanced tool developed actively monitors and manages coal quality and overall boiler conditions that maximizes availability and maintains generating capacity while reducing cost. The tool is used to forecast and alert plant operators and engineers about poor boiler conditions which may occur as a result of incoming coal and/or current power plant operating conditions. The Combustion System Performance Indices (CSPI) and CoalTracker (CT) programs predicts fireside performance of the plant including slagging, fouling, erosion, slag flow, strength development (sintering/densification), and slag layer thickness based on the composition of delivered coal. CT program is tailored for each plant and is used to track the coal from the point of delivery to the burner. The most successful application of the CSPI-CT has been at plants where the coal composition is determined through the use of a full stream elemental analyzers based on prompt gamma neutron analysis (PGNAA). The CSPI-CT program information is used by coal procurement, coal mining and plant operations personnel to select and blend coal properties for the best plant performance.

01 COAL, LIGNITE, AND PEAT↗

Remote sensing: Snow monitoring tool for today and tomorrow

Various types of remote sensing are now available or will be in the future for snowpack monitoring. Aircraft reconnaissance is now used in a conventional manner by various water resources agencies to obtain information on snowlines, depth, and melting of the snowpack for forecasting purposes. The use of earth resources satellites for mapping snowcovered area, snowlines, and changes in snowcover during the spring has increased during the last five years. Gamma ray aircraft flights, although confined to an extremely low altitude, provide a means for obtaining valuable information on snow water equivalent. The most recently developed remote sensing technology for snow, namely, microwave monitoring, has provided initial results that may eventually allow us to infer snow water equivalent or depth, snow wetness, and the hydrologic condition of the underlying soil.

Rango, A.↗

Remote-Sensing Time Series Analysis, a Vegetation Monitoring Tool

The Time Series Product Tool (TSPT) is software, developed in MATLAB , which creates and displays high signal-to- noise Vegetation Indices imagery and other higher-level products derived from remotely sensed data. This tool enables automated, rapid, large-scale regional surveillance of crops, forests, and other vegetation. TSPT temporally processes high-revisit-rate satellite imagery produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) and by other remote-sensing systems. Although MODIS imagery is acquired daily, cloudiness and other sources of noise can greatly reduce the effective temporal resolution. To improve cloud statistics, the TSPT combines MODIS data from multiple satellites (Aqua and Terra). The TSPT produces MODIS products as single time-frame and multitemporal change images, as time-series plots at a selected location, or as temporally processed image videos. Using the TSPT program, MODIS metadata is used to remove and/or correct bad and suspect data. Bad pixel removal, multiple satellite data fusion, and temporal processing techniques create high-quality plots and animated image video sequences that depict changes in vegetation greenness. This tool provides several temporal processing options not found in other comparable imaging software tools. Because the framework to generate and use other algorithms is established, small modifications to this tool will enable the use of a large range of remotely sensed data types. An effective remote-sensing crop monitoring system must be able to detect subtle changes in plant health in the earliest stages, before the effects of a disease outbreak or other adverse environmental conditions can become widespread and devastating. The integration of the time series analysis tool with ground-based information, soil types, crop types, meteorological data, and crop growth models in a Geographic Information System, could provide the foundation for a large-area crop-surveillance system that could identify a variety of plant phenomena and improve monitoring capabilities.

McKellip, Rodney↗

Optic Nerve Sheath Diameter: Translating a Terrestrial Focused Technique into a Clinical Monitoring Tool for Spaceflight

Ultrasonography is increasingly used to quickly measure optic nerve sheath diameter (ONSD) when increased intracranial pressure (ICP) is suspected. NASA Space and Clinical Operations Division has been using ground and on‐orbit ultrasound since 2009 as a proxy for ICP in non‐acute monitoring for space medicine purposes. In the terrestrial emergency room population, an ONSD greater than 0.59 cm is considered highly predictive of elevated intracranial pressure. However, this cut‐off limit is not applicable to the spaceflight setting since over 50% of US Operating Segment (USOS) astronauts have an ONSD greater than 0.60 cm even before launch. Crew Surgeon clinical decision‐making is complicated by the fact that many astronauts have history of previous spaceflights. Our data characterize the distribution of baseline ONSD in the astronaut corps, its longitudinal trends in long‐duration spaceflight, and the predictive power of this measure related to increased ICP outcomes.

Mason, Sara↗

G-PST Inertia Monitoring Tool [SWR-23-54]

This tool provides interfaces for ingesting real-time unit commitment data (e.g., from a grid operator's control room energy management system) and calculating system inertia estimates based on the H-constant method, before relaying those estimates to customizable visualization or logging outputs.

Stephen, Gordon↗

Open-Source Ambient-Signal-Based Inertia Monitoring Tool for Power systems [SWR-25-59]

This script, developed by NREL, implements an inertia estimation algorithm using a sliding window approach. The inertia (H) is estimated based on frequency deviations and active power deviations, utilizing the swing equation from power system dynamics. An example application is provided using the WECC 240-bus system.

Peng, Jiangkai [National Renewable Energy Laborato↗

Distributed Acoustic Sensing as a Monitoring Tool at LANL [Slides]

DAS records a variety of signals, including (1) earthquakes and volcanic eruptions, (2) explosions (DAG, mining, etc.), (3) acoustic waves, (4) ocean (waves, whales), (5) vehicle, ship and pedestrian traffic, (6) glaciology and landslides, and (7) oil and gas. Main questions include: (1) what is the extent of the signal content? (2) how does DAS compare to traditional sensors? (3) how do interrogators, fiber types, and fiber depth burials impact measurements? (4) special applications offshore to overcome the lack of instrumentation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Coordinating Aircraft During Field Campaigns: Real Time Mission Monitor Tool

RTMM has evolved into a powerful and easy to use application in support of planning, situational awareness and strategic decision-making during airborne field campaigns. NASA is very open to sharing these capabilities with any interested group through interagency collaborations in future field activities.

Goodman, Michael↗

Optic Nerve Sheath Diameter: Translating a Terrestrial Focused Technique Into a Clinical Monitoring Tool for Space Flight

Emergency medicine physicians recently adopted the use of ultrasonography to quickly measure optic nerve sheath diameter (ONSD) as concomitant with increased intracranial pressure. NASA Space and Clinical Operations Division has been using ground and on-orbit ultrasound capabilities since 2009 to consider this anatomical measure as a proxy for intracranial pressure in the microgravity environment. In the terrestrial emergency room population, an ONSD greater than 0.59 cm is considered highly predictive of elevated intracranial pressure. However, this cut-off limit is not applicable to the spaceflight setting since over 50% of US Operating Segment (USOS) astronauts have an ONSD greater than 0.60 cm even before missions. Crew Surgeon clinical decision-making is complicated by the fact that many astronauts have history of previous spaceflights. Data will be presented characterizing the distribution of baseline ONSD in the astronaut corps, longitudinal trends in-flight, and the predictive power of this measure related to increased intracranial pressure outcomes.

Mason, Sara S.↗