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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Evolution of the Data Quality Monitoring and Prompt Processing System in the proto DUNE-SP experiment

The DUNE Collaboration currently operates an experimental program based at CERN which includes a beam test and an extended cosmic ray run of two large-scale prototypes of the massive Liquid Argon Time Projection Chamber (LArTPC) for the DUNE Far Detector. The volume of data collected by the single-phase prototype (protoDUNE-SP) amounts to 3PB and the sustained rate of data sent to mass storage is O(100) MB/s. Data Quality Monitoring was implemented by directing a fraction of the data stream to the protoDUNE prompt processing system (p3s) which is optimized for continuous low-latency calculation of the vital detector metrics and various graphics including event displays. It served a crucial role throughout the life cycle of the experiment. We present our experience in leveraging the CERN computing environment and operating the system over an extended period of time, while adapting to evolving requirements and computing platform.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Electrical substation grid testbed for DLT applications of electrical fault detection, power quality monitoring, DERs use cases and cyber-events

Electrical utilities continue to deploy more intelligent electronic devices (IEDs) inside and outside electrical substation, and are associated with customer-owned distributed energy resources (DERs). The integrity and confidentiality of data from these IEDs, like power meters and protective relays, is crucial. Blockchain technology could improve the resilience of microgrids by improving the security of data sharing. The penetration of customer-owned DERs (renewable energy sources) and the increasing deployment of IEDs can lead to integrate power system applications with Distributed Ledger Technology (DLT). In this study, we implemented the electrical faulted phase detection and power quality monitoring algorithms with a Cyber Grid Guard (CGG) system using DLT. In addition, the DERs (wind turbine farms) use case and protective relay cyber-event tests were assessed, by using the CGG system with DLT. In the experimental model, the testbed was created by using a real-time simulator and CGG system with power meters/ protective relays in-the-loop. The data collected from the CGG system and IEDs were compared with the same time stamp source. These results had shown the successful assessment of protection, control and monitoring applications using a CGG system with DLT. In the future, the ESGT with DERs and the CGG system will be used in other power system applications, based on implementing smart contracts between electrical utilities with customer-owned DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2007

Colorimetric-Solid Phase Extraction Technology for Water Quality Monitoring: Evaluation of C-SPE and Debubbling Methods in Microgravity

Colorimetric-solid phase extraction (C-SPE) is being developed as a method for in-flight monitoring of spacecraft water quality. C-SPE is based on measuring the change in the diffuse reflectance spectrum of indicator disks following exposure to a water sample. Previous microgravity testing has shown that air bubbles suspended in water samples can cause uncertainty in the volume of liquid passed through the disks, leading to errors in the determination of water quality parameter concentrations. We report here the results of a recent series of C-9 microgravity experiments designed to evaluate manual manipulation as a means to collect bubble-free water samples of specified volumes from water sample bags containing up to 47% air. The effectiveness of manual manipulation was verified by comparing the results from C-SPE analyses of silver(I) and iodine performed in-flight using samples collected and debubbled in microgravity to those performed on-ground using bubble-free samples. The ground and flight results showed excellent agreement, demonstrating that manual manipulation is an effective means for collecting bubble-free water samples in microgravity.

Hazen-Bosveld, April↗
NASA NTRS2014

Performance Evaluation of the Operational Air Quality Monitor for Water Testing Aboard the International Space Station

Real-time environmental monitoring on ISS is necessary to provide data in a timely fashion and to help ensure astronaut health. Current real-time water TOC monitoring provides high-quality trending information, but compound-specific data is needed. The combination of ETV with the AQM showed that compounds of interest could be liberated from water and analyzed in the same manner as air sampling. Calibration of the AQM using water samples allowed for the quantitative analysis of ISS archival samples. Some calibration issues remain, but the excellent accuracy of DMSD indicates that ETV holds promise for as a sample introduction method for water analysis in spaceflight.

Wallace, William T.↗
NASA NTRS2011

A Study on the Potential Applications of Satellite Data in Air Quality Monitoring and Forecasting

In this study we explore the potential applications of MODIS (Moderate Resolution Imaging Spectroradiometer) -like satellite sensors in air quality research for some Asian regions. The MODIS aerosol optical thickness (AOT), NCEP global reanalysis meteorological data, and daily surface PM(sub 10) concentrations over China and Thailand from 2001 to 2009 were analyzed using simple and multiple regression models. The AOT-PM(sub 10) correlation demonstrates substantial seasonal and regional difference, likely reflecting variations in aerosol composition and atmospheric conditions, Meteorological factors, particularly relative humidity, were found to influence the AOT-PM(sub 10) relationship. Their inclusion in regression models leads to more accurate assessment of PM(sub 10) from space borne observations. We further introduced a simple method for employing the satellite data to empirically forecast surface particulate pollution, In general, AOT from the previous day (day 0) is used as a predicator variable, along with the forecasted meteorology for the following day (day 1), to predict the PM(sub 10) level for day 1. The contribution of regional transport is represented by backward trajectories combined with AOT. This method was evaluated through PM(sub 10) hindcasts for 2008-2009, using ohservations from 2005 to 2007 as a training data set to obtain model coefficients. For five big Chinese cities, over 50% of the hindcasts have percentage error less than or equal to 30%. Similar performance was achieved for cities in northern Thailand. The MODIS AOT data are responsible for at least part of the demonstrated forecasting skill. This method can be easily adapted for other regions, but is probably most useful for those having sparse ground monitoring networks or no access to sophisticated deterministic models. We also highlight several existing issues, including some inherent to a regression-based approach as exemplified by a case study for Beijing, Further studies will be necessa1Y before satellite data can see more extensive applications in the operational air quality monitoring and forecasting.

Li, Can↗
NASA NTRS1972

Acoustic emission used as weld quality monitor

Acoustic emission technique is described for use as quality control tool in nondestructive inspection of welds. Stress mounts around weld defect until it exceeds yield strength of material. Pressure wave relieving the stress is emitted and followed by oscillations caused by multiple reflections. Acoustic emissions are then detected by sensor similar to ultrasonic sensor.

Jolly, W. O.↗
NASA NTRSDate not supplied

Hyper-Spectral Infrared Remote Sensing for Wildfire-Related Research and Air Quality Monitoring

The National Airborne Sounder Testbed-Interferometer (NAST-I) is an airborne FTS remote sensor that nominally flies on NASA high-altitude aircraft to serve as a spaceborne instrument simulator. NAST-I continues to serve as a pathfinder for future satellite FTS systems and the next generation advanced atmospheric sounders in general. NAST-I provides high resolution spectrally resolved infrared radiances. NAST-I retrieval products characterizing the surface (i.e., skin temperature and spectral emissivity), atmosphere (i.e., profiles of temperature, moisture, ozone, carbon monoxide, and other trace species), and clouds (e.g., optical depth, particle size, temperature, and height) can be used to support fire-related monitoring and research. NAST-I provided 3-d characterizations of wildfire-induced plumes of CO during the FIREX-AQ field campaign (conducted during 2019) which showed the intensity and size evolution of wildfire plumes at high spatial and temporal resolutions. Wildfire-induced CO plumes, in conjunction with their evolution, transport, and age have been identified and recently published in scientific journals. Other research applications, such as surface emissivity changes due to fire burning of ground landscape, have been under investigation. These products could be used in support of wildfire management to better inform decision making and operations for pre-, active, and post-fire environments.

remote sensing↗
DOE OSTI2025

Data Quality Monitoring for the Hadron Calorimeters Using Transfer Learning for Anomaly Detection

The proliferation of sensors brings an immense volume of spatio-temporal (ST) data in many domains, including monitoring, diagnostics, and prognostics applications. Data curation is a time-consuming process for a large volume of data, making it challenging and expensive to deploy data analytics platforms in new environments. Transfer learning (TL) mechanisms promise to mitigate data sparsity and model complexity by utilizing pre-trained models for a new task. Despite the triumph of TL in fields like computer vision and natural language processing, efforts on complex ST models for anomaly detection (AD) applications are limited. In this study, we present the potential of TL within the context of high-dimensional ST AD with a hybrid autoencoder architecture, incorporating convolutional, graph, and recurrent neural networks. Motivated by the need for improved model accuracy and robustness, particularly in scenarios with limited training data on systems with thousands of sensors, this research investigates the transferability of models trained on different sections of the Hadron Calorimeter of the Compact Muon Solenoid experiment at CERN. The key contributions of the study include exploring TL’s potential and limitations within the context of encoder and decoder networks, revealing insights into model initialization and training configurations that enhance performance while substantially reducing trainable parameters and mitigating data contamination effects.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Morgan State University Air Quality Monitor Field Campaign Report

This activity was to enable us to install air quality and meteorological instrumentation such as an automated Air Quality Drone, PurpleAir Sensor, and Sensit Ramp Air Quality Sensor. This installation formed part of the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s Coast-Urban-Rural Atmospheric Gradient Experiment (CoURAGE) at the Baltimore site. Figure 1 shows the aerial image of the CoURAGE Baltimore site with all the installed instruments.

47 OTHER INSTRUMENTATION↗
NASA NTRS1990

Space Station Environmental Health System water quality monitoring

One of the unique aspects of the Space Station is that it will be a totally encapsulated environment and the air and water supplies will be reclaimed for reuse. The Environmental Health System, a subsystem of CHeCS (Crew Health Care System), must monitor the air and water on board the Space Station Freedom to verify that the quality is adequate for crew safety. Specifically, the Water Quality Subsystem will analyze the potable and hygiene water supplies regularly for organic, inorganic, particulate, and microbial contamination. The equipment selected to perform these analyses will be commercially available instruments which will be converted for use on board the Space Station Freedom. Therefore, the commercial hardware will be analyzed to identify the gravity dependent functions and modified to eliminate them. The selection, analysis, and conversion of the off-the-shelf equipment for monitoring the Space Station reclaimed water creates a challenging project for the Water Quality engineers and scientists.

Vincze, Johanna E.↗
NASA NTRS1979

Water Quality Monitor

In the photo above, the cylindrical container being lowered into the water is a water quality probe developed by NASA's Langley Research Center for the Environmental Protection Agency (EPA) in an applications engineering project. It is part of a system- which also includes recording equipment in the helicopter-for on-the-spot analysis of water samples. It gives EPA immediate and more accurate information than the earlier method, in which samples are transported to a lab for analysis. Designed primarily for rapid assessment of hazardous spills in coastal and inland waters, the system provides a wide range of biological and chemical information relative to water pollution.

Source record↗
NASA NTRS2022

Chesapeake Bay Water Resources: Characterization of Sediment Dynamics for Enhanced Water Quality Monitoring in the Chesapeake Bay

An increase in total suspended sediment (TSS) concentrations and turbidity have contributed to poor water quality in the Chesapeake Bay since the 1970s. Although turbidity and TSS have been moderately improving over the past few decades, poor water quality is detrimental to the Chesapeake Bay’s ecosystems and the surrounding watersheds. The Summer 2022 Chesapeake Bay Water Resources project observed sediment dynamics and turbidity in the York River watershed using remote sensing tools, models, and Earth observations including NASA and United States Geological Survey’s (USGS) Landsat satellite series, NASA DEVELOP’s Optical Reef Coastal Area Assessment Tool 2.0 (ORCAA), and Soil and Water Assessment Tool (SWAT). The collaborators on this project were the Chesapeake Bay National Estuarine Research Reserve (CBNERR), Group on Earth Observations (GEO) AquaWatch, the Committee on Earth Observation Satellites Coastal Observations, Applications, Services and Tools (CEOS COAST), and the Virginia Department of Environmental Quality (VA DEQ). The team concluded that the upstream sections of the York River watershed increased in TSS from 2009–2019. However, the seasonal TSS patterns often correlated with higher precipitation levels, although not necessarily major storm events. This may be due to factors like wind and waves contributing to the sedimentation trends observed. Although projects have been conducted to improve water quality, additional efforts like planting riparian buffers along areas with high TSS are needed to reduce the intensity of runoff. The team’s results will allow the end user, the VA DEQ, to inform their policymaking regarding future Bay conservation efforts.

Katherine Hahn↗
NASA NTRS2013

Toward the Next Generation of Air Quality Monitoring Indicators

This paper introduces an initiative to bridge the state of scientific knowledge on air pollution with the needs of policymakers and stakeholders to design the "next generation" of air quality indicators. As a first step this initiative assesses current monitoring and modeling associated with a number of important pollutants with an eye toward identifying knowledge gaps and scientific needs that are a barrier to reducing air pollution impacts on human and ecosystem health across the globe. Four outdoor air pollutants were considered e particulate matter, ozone, mercury, and Persistent Organic Pollutants (POPs) e because of their clear adverse impacts on human and ecosystem health and because of the availability of baseline data for assessment for each. While other papers appearing in this issue will address each pollutant separately, this paper serves as a summary of the initiative and presents recommendations for needed investments to provide improved measurement, monitoring, and modeling data for policyrelevant indicators. The ultimate goal of this effort is to enable enhanced public policy responses to air pollution by linking improved data and measurement methods to decision-making through the development of indicators that can allow policymakers to better understand the impacts of air pollution and, along with source attribution based on modeling and measurements, facilitate improved policies to solve it. The development of indicators represents a crucial next step in this process.

Particulate matter↗
NASA NTRS1979

Multidate Landsat lake quality monitoring program

A unified package of files and programs has been developed to automate the multidate Landsat-derived analyses of water quality for about 3000 inland lakes throughout Wisconsin. A master lakes file which stores geographic information on the lakes, a file giving the latitudes and longitudes of control points for scene navigation, and a program to estimate control point locations and produce microfiche character maps for scene navigation are among the files and programs of the system. The use of ground coordinate systems to isolate irregular shaped areas which can be accessed at will appears to provide an economical means of restricting the size of the data set.

Fisher, L. T.↗
NASA NTRS1977

Landsat change detection can aid in water quality monitoring

Comparison between Landsat-1 and -2 imagery of Arkansas provided evidence of significant land use changes during the 1972-75 time period. Analysis of Arkansas historical water quality information has shown conclusively that whereas point source pollution generally can be detected by use of water quality data collected by state and federal agencies, sampling methodologies for nonpoint source contamination attributable to surface runoff are totally inadequate. The expensive undertaking of monitoring all nonpoint sources for numerous watersheds can be lessened by implementing Landsat change detection analyses.

Macdonald, H. C.↗