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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Deriving Essential Climate Variable Data from Multiple Satellite Remote Sensors Using a Consistent Fingerprinting Method

Hyperspectral observations from satellite-based sensors provide high information content for the Earth’s atmospheric and surface properties. Traditionally, long-term climate products are derived by performing spatial and temporal averaging of level-2 satellite products. It is a time-consuming process to generate level-2 data products since modern hyperspectral satellite sensors have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in level-2 retrieval algorithms can lead to errors in the climate products when fusing data from different satellite sensors. We have developed a radiometrically consistent spectral fingerprinting method, which overcomes the above-mentioned shortcomings, to derive climate change signals from multiple satellite sensors using spatiotemporally averaged level-1 data. We have applied this method to Atmospheric Infrared Sounder (AIRS) and Cross-track Infrared Sounder (CrIS) data and generated decade-long climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. A key component to this work is a set of observational-based radiative kernels produced from CrIS level-1 data using a single field of view (SFOV) optimal estimation retrieval algorithm. Only limited CrIS level-1 data (e.g., 1-2 years of data) are needed to the derive radiative kernels. Our Principal Component-based Radiative Model (PCRTM) enables us to perform SFOV retrievals under all sky conditions and provides radiative kernels (including those for clouds) needed by the spectral fingerprinting method. In this presentation, we will describe the basic methodology, the details of the algorithm, and results from NASA Aqua AIRS and Suomi-NPP CrIS data. The method can be applied to study future hyperspectral remote sensors such as CLARREO (Climate Absolute Radiance and Refractivity Observatory) Pathfinder (CPF), Tropospheric Emissions: Monitoring of Pollution (TEMPO), Surface Biology and Geology (SBG), Aerosol and Cloud, Convection and Precipitation (ACCP).

Xu Liu↗
DOE OSTI2024

A data-driven sensor placement approach for detecting voltage violations in distribution systems

Stochastic fluctuations in power injections from distributed energy resources (DERs) combined with load variability can cause constraint violations (e.g., exceeded voltage limits) in electric distribution systems. To monitor grid operations, sensors are placed to measure important quantities such as the voltage magnitudes. Here, in this paper, we consider a sensor placement problem which seeks to identify locations for installing sensors that can capture all possible violations of voltage magnitude limits. We formulate a bilevel optimization problem that minimizes the number of sensors and avoids false sensor alarms in the upper level while ensuring detection of any voltage violations in the lower level. This problem is challenging due to the nonlinearity of the power flow equations and the presence of binary variables. Accordingly, we employ recently developed conservative linear approximations of the power flow equations that overestimate or underestimate the voltage magnitudes. By replacing the nonlinear power flow equations with conservative linear approximations, we can ensure that the resulting sensor locations and thresholds are sufficient to identify any constraint violations. Additionally, we apply various problem reformulations to significantly improve computational tractability while simultaneously ensuring an appropriate placement of sensors. Lastly, we improve the quality of the results via an approximate gradient descent method that adjusts the sensor thresholds. We demonstrate the effectiveness of our proposed method for several test cases, including a system with multiple switching configurations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2011

Airborne Remote Observations of L-Band Radio Frequency Interference and Implications for Satellite Missions

Passive remote sensing of the Earth s surface and atmosphere from space has significant importance in operational and research environmental studies, in particular for the scientific understanding, monitoring and prediction of climate change and its impacts. Passive remote sensing requires the measurement of naturally occurring radiations, usually of very low power levels, which contain essential information on the physical process under investigation. As such, these sensed radio frequency bands are a unique natural resource enabling space borne passive sensing of the atmosphere and the Earth s surface that deserves adequate allocation to the Earth Exploration Satellite Service and absolute protection from interference. Unfortunately, radio frequency interference (RFI) is an increasing problem for Earth remote sensing, particularly for passive observations of natural emissions. Because these natural signals tend to be very weak, even low levels of interference received by a passive sensor may degrade the fidelity of scientific data. The characteristics of RFI (low-level interference and radar-pulse noise) are not well known because there has been no systematic surveillance, spectrum inventory or mapping of RFI. While conducting a flight experiment over central Tennessee in May 2010, RFI, a concern for any instrument operating in the passive L band frequency, was observed across 16 subbands between 1402-1427 MHz. Such a survey provides rare characterization data from which to further develop mitigation technologies as well as to identify bandwidths to avoid in future sensor formulation.

Laymon, Charles↗
NASA NTRS1993

Process Analyzer

Under a NASA Small Business Innovation Research (SBIR) contract, Axiomatics Corporation developed a shunting Dielectric Sensor to determine the nutrient level and analyze plant nutrient solutions in the CELSS, NASA's space life support program. (CELSS is an experimental facility investigating closed-cycle plant growth and food processing for long duration manned missions.) The DiComp system incorporates a shunt electrode and is especially sensitive to changes in dielectric property changes in materials at measurements much lower than conventional sensors. The analyzer has exceptional capabilities for predicting composition of liquid streams or reactions. It measures concentrations and solids content up to 100 percent in applications like agricultural products, petrochemicals, food and beverages. The sensor is easily installed; maintenance is low, and it can be calibrated on line. The software automates data collection and analysis.

Source record↗
DOE OSTI2018

Graphene-elastomer nanocomposites based flexible piezoresistive sensors for strain and pressure detection

Highlights: • Fabricating flexible piezoresistive sensors based on PDMS/GNPs nanocomposites. • Positive strain sensitive capacity occurs during increasing pressure-loading process but before the threshold of forces loading. • Tunable strain and pressure sensitivity are achieved by controlling GNPs incorporation, and improved to 140 and 260 at 5 wt% GNPs respectively. • Superior dynamic correspondence with applied pressure and relatively high repeatability. • Application of the GNPs/PDMS piezoresistive sensors as detecting the finger motions. - Abstract: Strain and pressure sensitive flexible piezoresistive sensors have been fabricated based on nanocomposites of graphene nanoplatelets (GNPs) and Polydimethylsiloxane (PDMS) elastomer. The strain detective sensors show positive piezoresistive characteristic under diverse levels of static strain up to 20% due to the flexibility and stretchability of PDMS elastomer. Tunable strain sensitivity of GNPs/PDMS piezoresistive sensors can be achieved by controlling GNPs incorporation into PDMS elastomer, which will be improved to 140 at 5 wt% GNPs concentration. In addition, pressure sensitive response, which exists when the pressure loading is less than threshold pressure, also can be observed in GNPs/PDMS piezoresistive sensors. The GNPs network-elastomer nanocomposite based pressure sensors show tunable piezoresistivity in the ranges of ∼260 under increasingly higher GNPs concentrations. During the cyclic pressure loading, the pressure sensitive behavior of GNPs/PDMS nanocomposites manifests a superior dynamic correspondence with applied pressure while the resistance response can retain at a relatively high level under multiple loading-unloading cycles. Since the GNPs/PDMS piezoresistive sensors can not only respond to subtle bending but also distinguish them accurately for detecting the finger motions, it will make the GNPs/PDMS nanocomposite a good candidate for artificial skin and wearable sensor applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Development Plan for Ultrasonic Pressure Sensors [Slides]

Current light water reactors (LWRs) utilize differential pressure cells, based on strain gauges, which are remotely located from the reactor vessel via impulse lines. These pressure sensors are used to measure liquid level within the vessel and to give a general indication of system health with regard to leaks and flow system fouling. The advanced reactor types currently under development generally operate at higher temperatures than light-water reactors and utilize coolants that may be highly corrosive (i.e., liquid metals). They will use pressure measurements for varied measurands, such as level and flow rate, as well as indications of accident conditions or off-normal operating conditions. More robust pressure sensors are needed to address these more challenging conditions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1974

Flame detector operable in presence of proton radiation

A detector of ultraviolet radiation for operation in a space vehicle which orbits through high intensity radiation areas is described. Two identical ultraviolet sensor tubes are mounted within a shield which limits to acceptable levels the amount of proton radiation reaching the sensor tubes. The shield has an opening which permits ultraviolet radiation to reach one of the sensing tubes. The shield keeps ultraviolet radiation from reaching the other sensor tube, designated the reference tube. The circuitry of the detector subtracts the output of the reference tube from the output of the sensing tube, and any portion of the output of the sensing tube which is due to proton radiation is offset by the output of the reference tube. A delay circuit in the detector prevents false alarms by keeping statistical variations in the proton radiation sensed by the two sensor tubes from developing an output signal.

Walker, D. J.↗
DOE OSTI2018

Synthesis and gas sensing properties of NiO/SnO2 hierarchical structures toward ppb-level acetone detection

Highlights: • The NiO/SnO{sub 2} hierarchical structures with different Ni contents have been prepared by facile hydrothermal method. • The NiO/SnO{sub 2} sensors exhibit the enhanced gas sensing performances comparing with pure SnO{sub 2}. • The Ni{sub 1}Sn{sub 3} sensor exhibits higher response, fast response/recovery time for acetone detection. - Abstract: We have synthesized pristine SnO{sub 2} and NiO/SnO{sub 2} hierarchical structures by a facile hydrothermal method. Structural and morphological characterizations of the obtained NiO/SnO{sub 2} samples were systematically studied using XRD, SEM, TEM and XPS. Meanwhile, gas-sensing properties of the as-fabricated pristine SnO{sub 2} and NiO/SnO{sub 2} sensor devices were investigated toward ppb-level acetone detection. The measured results show that the Ni{sub 1}Sn{sub 3} gas sensor can reach a response of 20.18 toward 50 ppm acetone under optimum operating temperature (300 °C), which is about 3.3 times higher than that of pristine sensor. Moreover, the Ni{sub 1}Sn{sub 3} gas sensor also exhibits fast response/recovery time (2 s/9 s), low detection limit (10 ppb) and good selectivity. We attribute the enhanced gas-sensing properties of NiO/SnO{sub 2} hierarchical structures to the synergetic effect as well as p-n heterojunction between the NiO and SnO{sub 2} structures.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Calibration and field deployment of low-cost sensor network to monitor underground pipeline leakage

Recent technological advances in methane detection have improved leak detection and repair. However, current methods to reliably measure methane concentrations rely on expensive instruments or demand significant labor input. There is interest in using affordable methane sensors that are responsive to ppmv level changes in methane concentrations in both urban and rural environments for monitoring underground natural gas pipeline leaks. This is especially relevant for situations where potentially significant leaks cannot be repaired immediately or smaller leaks that require long-term monitoring and further evaluation. In this work, a low-cost sensor unit, equipped with a metal oxide sensor, was designed, built, and calibrated over a wide range of methane concentrations and environmental conditions in preparation for field application. A network of these sensors was then installed at the test site and used to measure methane concentrations at ground level above known sub-surface natural gas emissions which emulated underground gas pipeline leaks. This low-cost sensor network measured over 4 days total for the two different known leakage rates. Results demonstrate that the sensors can continuously measure relative methane variability for extended periods but require calibration for a wide range of temperature and humidity conditions to properly determine absolute gas (i.e., methane) concentrations. Furthermore, when a regression analysis was conducted to evaluate the effects of meteorological parameters on methane concentration, air temperature and wind speed have strong impacts on the concentration. Overall, the network approach allows improved identification of leak location and monitoring of underground natural gas leaks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Electrodermal activity as a proxy for sweat rate monitoring during physical and mental activities

Electrodermal activity has long been used for mental activity monitoring by measuring skin conductance at specific locations, such as fingertips, with high sweat gland density. However, electrodermal activity has not been considered useful for physical activity monitoring, where large sweat volumes are generated, resulting in the accumulation of sweat at the skin–electrode interface and, thus, preventing further dynamic response to sweating events. Here we show that electrodermal activity can be used as a proxy for sweat loss measurement under both low and high physical activity levels. We use wearable sweat sensors that consist of water-permeable electrodes and microfluidic-based sweat analysers, and show that skin conductance is proportional to the instantaneous sweat loss. We demonstrate that sweat loss during exercise can be estimated by integrating skin conductance over time, which can be applied to assess the body hydration status of exercisers. From multisite measurements of skin conductance, we show that the wrist, forearm and upper arm are reflective of physical activity levels, whereas the finger is indicative of mental activity. Simultaneous measurement of two different sites selectively decouples mental and physical activities.

Biomedical engineering↗
NASA NTRS1994

Using Si Diodes To Detect H2 Liquid/Vapor Interfaces

Commercially available silicon-diode temperature sensors used to detect interfaces between hydrogen liquid and hydrogen vapor at steady-state saturation conditions. Sensors mounted at short intervals along rod to form rake-like array. Array inserted in tank with rod oriented vertically, where it senses level of liquid hydrogen to resolution equal to interval between sensors. Basic idea to measure voltage across sensor while supplying small electric current that heats sensor. Because vapor cools sensor less effectively than liquid does, sensor's steady-state temperature greater when sensor surrounded by vapor than when immersed in liquid. Voltage output decreases as temperature increases for silicon diodes. Thus, temperature (voltage) reading used to determine whether liquid level above or below sensor.

Dempsey, Paula Jean↗
NASA NTRS1990

Sub-visual Cirrus detection and characterization

Analysis of archived cold optics (COR) radiometer data is yielding useful information on the diurnal, geographic, seasonal and altitude variability of atmospheric background radiance levels in the 11 micron window region. This database is a compilation of Kuiper Infrared Technology Experiment (KITE) and Atmospheric Radiance Study (ARS) observations under a wide variety of conditions. Correlating the measurements from these two studies with the LOWTRAN model code has revealed several important results. First, the 11 micron window appears to be filled-in, i.e., the troughs on either side of the nitric acid peak are shallower than expected. Second, the amplitude of the background radiances measured exceeds the model predictions by a factor of 2 to 3 or more. This is thought to be due to the existence of thin, high altitude cirrus clouds (sub-visual cirrus) above the sensor platform. These high background levels are observed under quiescent conditions in the South Pacific (Marshall Islands), as well as over the continental United States (the West Coast). In the tropics, there appears to be little diurnal variability, a plausible seasonal variation and a linear dependence between 7.2 and 11.4 micron band data, indicating possible multi-spectral approaches to detection of sub-visual cirrus clouds. Theoretical analysis of the magnitude of the effects of a sub-visual cirrus cloud on atmospheric background radiances measured by a near-horizontal sensor is in progress.

Schmidt, E.↗
NASA NTRS2015

System Design and Locomotion of Superball, an Untethered Tensegrity Robot

The Spherical Underactuated Planetary Exploration Robot ball (SUPERball) is an ongoing project within NASA Ames Research Center's Intelligent Robotics Group and the Dynamic Tensegrity Robotics Lab (DTRL). The current SUPERball is the first full prototype of this tensegrity robot platform, eventually destined for space exploration missions. This work, building on prior published discussions of individual components, presents the fully-constructed robot. Various design improvements are discussed, as well as testing results of the sensors and actuators that illustrate system performance. Basic low-level motor position controls are implemented and validated against sensor data, which show SUPERball to be uniquely suited for highly dynamic state trajectory tracking. Finally, SUPERball is shown in a simple example of locomotion. This implementation of a basic motion primitive shows SUPERball in untethered control.

Tensegrity↗
DOE OSTI2019

Performance of CMOS pixel sensor prototypes in ams H35 and aH18 technology for the ATLAS ITk upgrade

Pixel sensors based on commercial high-voltage CMOS processes are an exciting technology that is considered as an option for the outer layer of the ATLAS inner tracker upgrade at the High Luminosity LHC. Here, charged particles are detected using deep n-wells as sensor diodes with the depleted region extending into the silicon bulk. Both analog and digital readout electronics can be added to achieve different levels of integration up to a fully monolithic sensor. Small scale prototypes using the ams CMOS technology have previously demonstrated that it can achieve the required radiation tolerance of 10(15) n(eq)/cm(2) and detection efficiencies above 99.5%. Recently, large area prototypes, comparable in size to a full sensor, have been produced that include most features required towards a final design: the H35demo prototype produced in ams H35 technology that supports both external and integrated readout and the monolithic ATLASPix1 pre-production design produced in ams aH18 technology. Both chips are based on large fill-factor pixel designs, but differ in readout structure. Performance results for H35DEMO with capacitively-coupled external readout and first results for the monolithic ATLASPix1 are shown.

ATLAS ITk upgrade↗
DOE OSTI2017

Severe accident: hardening of standards and qualification requirements for nuclear pressure transmitters - 319

Nuclear power stations are designed according to the nuclear safety principle: the achievement of proper operating conditions, prevention of accidents or mitigation of accident consequences, resulting in protection of workers, the public and the environment from undue radiation hazards. This principle is applicable from the design to the dismantling of the power station, including normal and accident (and post-accident) operation. To take into account the world experience (incident or accident as Fukushima), international safety authorities recommends to reinforce safety functions and qualification requirements level. Concerning the instrumentation, devices like sensors are mainly impacted by the following constraint improvements: - Radiation resistance in normal and accident conditions: - Higher total dose; - Dose Rate; - Nature of radiation; - Pressure and Temperature profile in terms of: - Magnitude of pressure and / or temperature (higher); - Duration of higher constraints (longer). All these specifications induce: - The creation of a new qualification level - Severe Accident (SA) or equivalent; - An impact on the sensor technology to improve the resistance to harsh environment. Finally, the paper will present in details the evolution of the requirements and will sum up the advantages and disadvantages of different technologies to meet the severe accident conditions. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Multiscale and Multivariate Transportation System Visualization for Shopping District Traffic and Regional Traffic

In this paper, we present a suite of visualization techniques for sensor-based transportation system data at different scales to facilitate the exploration of interconnected traffic dynamics at intersections and highways. Additionally, these techniques are designed for analyzing multivariate traffic data from radar-based highway sensors and camera-based intersection sensors recording turn movements and vehicle speed, in the Chattanooga Metropolitan Area, with the capability of (a) revealing multiscale mobility patterns using different levels of data aggregation (e.g., individual sensor for microscale, multiple sensors along a corridor for mesoscale, and a larger number of sensors across the region for macroscale visualization) at different intervals (e.g., 5-min intervals, time of day, full day, and day-of-the-week), and (b) exploring the spatial variation of multiple traffic-related variables (e.g., volumes, speeds, turn movements, and traffic light colors) provided by the sensors. We close with a case study to demonstrate the effectiveness of our multiscale and multivariate visualization techniques. At microscale, we focused on intersection data from a shopping district around Shallowford Road in East Chattanooga. For mesoscale visualization, we studied the Shallowford Road corridor and an adjacent stretch of I-75. At macroscale, we included highway data from the Chattanooga Metropolitan Area. All visualizations were integrated into a web-based situational awareness tool to promote user access and interaction. At a minimum, each visualization provides the option for selecting dates for real-time (depending on sensor availability) and historical data, and additional information on hovering, though most provide more detailed information, including different views of the selected data, or interactive highlights.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1988

Debris prevention analysis for DFI/OFI/OEI (STS-26 configuration only)

The first 3 shuttle flights to use the Redesigned Solid Rocket Motors (RSRMs) will utilize Development Flight Instrumentation (DFI), as well as Operational Flight Instrumentation (OFI), and Operational Environment Instrumentation (OEI). The OFI consists of high pressure transducers used on both RSRMs to monitor the igniter and motor chamber pressure. DFI consists of assorted strain gages, temperature sensors, accelerometers, girth gages, and low level pressure transducers. The latter are installed on the left hand booster to measure post-separation aerodynamic loading. OEI consistes of temperature sensors. After Flight 3, all DFI gages are to be deleted, and only OFI and OEI will be used for subsequent flights. This report deals specifically with debris prevention and hazards concernig the STS-26 flight DFI configuration only. Continued analysis is being done that will adequately address the debris hazards associated with the STS-27 and subsequent flight DFI configurations.

Richi, Glen A.↗
NASA NTRSDate not supplied

Generating Essential Climate Variables from Multiple Satellite Hyperspectral Remote Sensors

Hyperspectral observations from satellite-based sensors provide high information content for the Earth’s atmospheric and surface properties. Traditionally, long-term climate products are derived by performing spatial and temporal averaging of level-2 satellite products. There are two shortcomings of this approach. First, it is a time-consuming process to generate level-2 data products since modern hyperspectral satellite sensors have millions of observations each day with thousands of spectral channels for each observation. Secondly, differences in level-2 retrieval algorithms can lead to errors in the fused multi-satellite data. We have developed a radiometrically consistent spectral fingerprinting method, which overcomes the above-mentioned shortcomings, to derive climate change signals from multiple satellite sensors using spatiotemporally averaged level-1 data. We have applied this method to data collected from Atmospheric Infrared Sounder (AIRS) on Aqua satellite and Cross-track Infrared Sounder (CrIS) on SNPP and NOAA20 and generated decade-long climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. A key component to this work is a set of observational-based radiative kernels produced from CrIS level-1 data using a single field of view (SFOV) optimal estimation retrieval algorithm. Only limited CrIS level-1 data (e.g., 1-2 years of data) are needed to the derive radiative kernels. Our Principal Component-based Radiative Model (PCRTM) enables us to perform SFOV retrievals under all sky conditions and provides radiative kernels (including those for clouds) needed by the spectral fingerprinting method. In this presentation, we will describe the basic methodology, the details of the algorithm, and results from NASA Aqua AIRS and Suomi-NPP CrIS data. The method can be applied to study future hyperspectral remote sensors such as CLARREO (Climate Absolute Radiance and Refractivity Observatory) Pathfinder (CPF), Tropospheric Emissions: Monitoring of Pollution (TEMPO), Surface Biology and Geology (SBG), Atmosphere Observing System (AOS).

Xu Liu↗