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At least 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Monitoring of Structural Integrity of Composite Structures by Embedded Optical Fiber Sensors

Real time monitoring of the mechanical integrity and stresses on key aerospace composite structures like aircraft wings, walls of pressure vessels and fuel tanks or any other structurally extended components and panels as in space telescopes is very important to NASA. Future military and commercial aircraft as well as NASA space systems such as Space Based Radar and International Space Station will incorporate a monitoring system to sense any degradation to the structure. In the extreme flight conditions of an aerospace vehicle it might be desirable to measure the strain every ten centimeters and thus fully map out the strain field of a composite component. A series of missions and vehicle health management requirements call for these measurements. At the moment thousands of people support a few vehicle launches per year. This number can be significantly reduced by implementing intelligent vehicles with integral nervous systems (smart structures). This would require maintenance to be performed only as needed. Military and commercial aircrafts have an equally compelling case. Maintenance yearly costs are currently reaching astronomical heights. Monitoring techniques are therefore required that allow for maintenance to be performed only when needed. This would allow improved safety by insuring that necessary tasks are performed while reducing costs by eliminating procedures that are costly and not needed. The advantages fiber optical sensors have over conventional electro-mechanical systems like strain gauges have been widely extolled in the research literature. These advantages include their small size, low weight, immunity to electrical resistance, corrosion resistance, compatibility with composite materials and process conditions, and multiplexing capabilities. One fiber optic device which is suitable for distributed sensing is the fiber Bragg grating (FBG). Researchers at NASA MSFC are currently developing techniques for using FBGs for monitoring the integrity of advanced structural materials expected to become the mainstay of the current and future generation space structures. Since carbon-epoxy composites are the materials of choice for the current space structures, the initial study is concentrated on this type of composite. The goals of this activity are to use embedded FBG sensors for measuring strain and temperature of composite structures, and to investigate the effects of various parameters such as composite fiber orientation with respect to the optical sensor, unidirectional fiber composite, fabrication process etc., on the optical performance of the sensor. This paper describes an experiment to demonstrate the use of an embedded FBG for measuring strain in a composite material. The performance of the fiber optic sensor is determined by direct comparison with results from more conventional instrumentation.

Albert J. Osei↗
NASA NTRS1970

Radar monitoring of oil pollution

Radar is currently used for detecting and monitoring oil slicks on the sea surface. The four-frequency radar system is used to acquire synthetic aperature imagery of the sea surface on which the oil slicks appear as a nonreflecting area on the surface surrounded by the usual sea return. The value of this technique was demonstrated, when the four-frequency radar system was used to image the oil spill of tanker which has wrecked. Imagery was acquired on both linear polarization (horizontal, vertical) for frequencies of 428, 1228, and 8910 megahertz. Vertical returns strongly indicated the presence of oil while horizontal returns failed to detect the slicks. Such a result is characteristic of the return from the sea and cannot presently be interpreted as characteristics of oil spills. Because an airborne imaging radar is capable of providing a wide-swath coverage under almost all weather conditions, it offers promise in the development of a pollution-monitoring system that can provide a coastal watch for oil slicks.

Guinard, N. W.↗
NASA NTRS2003

A Scintillation Counter System Design To Detect Antiproton Annihilation using the High Performance Antiproton Trap(HiPAT)

The High Performance Antiproton Trap (HiPAT), a system designed to hold up to l0(exp 12) charge particles with a storage half-life of approximately 18 days, is a tool to support basic antimatter research. NASA's interest stems from the energy density represented by the annihilation of matter with antimatter, 10(exp 2)MJ/g. The HiPAT is configured with a Penning-Malmberg style electromagnetic confinement region with field strengths up to 4 Tesla, and 20kV. To date a series of normal matter experiments, using positive and negative ions, have been performed evaluating the designs performance prior to operations with antiprotons. The primary methods of detecting and monitoring stored normal matter ions and antiprotons within the trap includes a destructive extraction technique that makes use of a micro channel plate (MCP) device and a non-destractive radio frequency scheme tuned to key particle frequencies. However, an independent means of detecting stored antiprotons is possible by making use of the actual annihilation products as a unique indicator. The immediate yield of the annihilation event includes photons and pie mesons, emanating spherically from the point of annihilation. To "count" these events, a hardware system of scintillators, discriminators, coincident meters and multi channel scalars (MCS) have been configured to surround much of the HiPAT. Signal coincidence with voting logic is an essential part of this system, necessary to weed out the single cosmic ray events from the multi-particle annihilation shower. This system can be operated in a variety of modes accommodating various conditions. The first is a low-speed sampling interval that monitors the background loss or "evaporation" rate of antiprotons held in the trap during long storage periods; provides an independent method of validating particle lifetimes. The second is a high-speed sample rate accumulating information on a microseconds time-scale; useful when trapped antiparticles are extracted against a target, providing an indication of quantity. This paper details the layout of this system, setup of the hardware components around HiPAT, and applicable checkouts using normal matter radioactive sources.

Martin, James J.↗
NASA NTRS2013

Comparative Study of Vibration Condition Indicators for Detecting Cracks in Spur Gears

This paper reports the results of an empirical study on the tooth breakage failure mode in spur gears. Of four dominant gear failure modes (breakage, wear, pitting, and scoring), tooth breakage is the most precipitous and often leads to catastrophic failures. The cracks were initiated using a fatigue tester and a custom-designed single-tooth bending fixture to simulate over-load conditions, instead of traditional notching using wire electrical discharge machining (EDM). The cracks were then propagated on a dynamometer. The ground truth of damage level during crack propagation was monitored with crack-propagation sensors. Ten crack propagations have been performed to compare the existing condition indicators (CIs) with respect to their: ability to detect a crack, ability to assess the damage, and sensitivity to sensor placement. Of more than thirty computed CIs, this paper compares five commonly used: raw RMS, FM0, NA4, raw kurtosis, and NP4. The performance of combined CIs was also investigated, using linear, logistic, and boosted regression trees based feature fusion.

Nanadic, Nenad↗
NASA NTRS2000

The Impact of Sea-Surface Winds on Meteorological Conditions in Israel: An Initial Study

The SSM/I (Spectral Sensor Microwave Imager) dataset is used to monitor surface wind speed and direction at four locations over the Eastern Mediterranean during December 1998 - January 1999. Time series of these data are compared to concurrent series of precipitation, surface temperature, humidity and winds at selected Israeli stations: Sde Dov (coastal), Bet Dagan (5 km. inland), Jerusalem (Judean Hills), Hafetz Haim (3 km. inland) and Sde Boker (central Negev). December 1998 and the beginning of January 1999 were dry in Israel, but significant precipitation was recorded at many stations during the second half of January (1999). SSM/I data show a surge in westerly surface winds west of Israel (32 N, 32.5 E) on 15 January, coinciding with the renewal of precipitation. We discuss the relevant circulation and pressure patterns during this transition in the context of the evolving meteorological conditions at the selected Israeli locations. The SSM/I dataset of near ocean surface winds, available for the last 12 years, is described. We analyze lagged correlation between these data and the Israeli station data and investigate possibility of predictive skill. Application of such relationships to short-term weather prediction would require real-time access to the SSM/I observations.

Otterman, J.↗
NASA NTRS1992

Intelligent sensor-model automated control of PMR-15 autoclave processing

An intelligent sensor model system has been built and used for automated control of the PMR-15 cure process in the autoclave. The system uses frequency-dependent FM sensing (FDEMS), the Loos processing model, and the Air Force QPAL intelligent software shell. The Loos model is used to predict and optimize the cure process including the time-temperature dependence of the extent of reaction, flow, and part consolidation. The FDEMS sensing system in turn monitors, in situ, the removal of solvent, changes in the viscosity, reaction advancement and cure completion in the mold continuously throughout the processing cycle. The sensor information is compared with the optimum processing conditions from the model. The QPAL composite cure control system allows comparison of the sensor monitoring with the model predictions to be broken down into a series of discrete steps and provides a language for making decisions on what to do next regarding time-temperature and pressure.

Hart, S.↗
NASA NTRS2016

Tracking On-Orbit Stability of the Response Versus Scan Angle for the S-NPP VIIRS Reflective Solar Bands

The Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi NPP (National Polar-orbiting Partnership) satellite (http:npp.gsfc.nasa.govviirs.html) has been in operation for nearly five years. The onboard calibration of the VIIRS reflective solar bands (RSB) relies on a solar diffuser (SD) located at a fixed scan angle and a solar diffuser stability monitor (SDSM). The VIIRS response versus scan angle (RVS) was characterized prelaunch in ambient conditions and is currently used to determine the on-orbit response for all scan angles relative to the SD scan angle. Since the RVS is vitally important to the quality of calibrated level 1B products, it is important to monitor its on-orbit stability. In this study, the RVS stability is examined based on reflectance trends collected from 16-day repeatable orbits over pre-selected pseudo-invariant desert sites in Northern Africa. These trends nearly cover the entire Earth view scan range so that any systematic drifts in the scan angle direction would indicate a change in RVS. This study also compares VIIRS RVS on-orbit stability results with those from both Aqua and Terra MODIS over the first four years of mission for a few selected bands, which provides further information on potential VIIRS RVS on-orbit changes.

Wu, Aisheng↗
DOE OSTI2024

Integration of Condition-Based, Diagnostic, Prognostic, And Anomaly Detection Data into Reliability Models to Support a Predictive Maintenance Context

Reliability data employed in plant reliability models are an approximated integral representation of the past industrywide operational experience, and they neglect the present asset health status (available, for example, from online monitoring data and diagnostic assessments) and forecasted health projection (when available from prognostic models). Ideally, in a predictive maintenance context, system reliability models should support decision making by propagating actual health information from the asset to the system level in order to provide a quantitative snapshot of system health and identify the most critical assets. Asset health should be informed solely by that specific asset’s current and historical performance data and should not be an approximated integral representation of the past industrywide operational experience (as currently performed by system reliability models through Bayesian updating processes). This paper proposes a reliability modeling approach that relies on asset diagnostic and prognostic assessments, along with monitoring data to measure asset health. We show how state-of-the art condition-based, diagnostic, prognostic, and anomaly detection models can be linked to system reliability models not in probability terms, but in terms of margin where margin is defined as the “distance” between the present status and an undesired event (e.g., failure or unacceptable performance). Then, we show how the propagation of margin data from the asset to the system level is performed through classical reliability models such as fault trees or reliability block diagrams. The described method is in fact able to propagate heterogenous health data from the asset to the system level in order to analytically assess system health.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Principal Component and Machine Learning Approach to Gap Fill Hyperspectral Ocean Color Satellite Retrievals

Retrievals of ocean color properties from space are important for monitoring the health of the ocean ecosystem but such retrievals can be limited spatially due to conditions such as clouds, aerosols, and sun glint. Gap filling of ocean color retrievals is typically performed by combining retrievals from multiple satellites or temporally averaging multiple days of retrievals. Despite these techniques large gaps still exist posing challenges for near real time monitoring of events like harmful algae blooms. To address these limitations, we developed a spatial gap filling approach applying machine learning approach to hyperspectral instruments to learn how to perform an atmospheric correction under challenging retrieval conditions. In this approach a principal component analysis is used to decompose the hyperspectral measurements into spectral components that describe the scattering and absorption of the atmosphere mixed with the surface spectral signatures. The coefficients of the principal components are used to train a neural network to predict ocean color properties derived from a standard MODIS ocean color algorithm. We apply the approach to two hyperspectral UV/VIS sensors, the Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) to show that it can be used to estimate ocean color properties such as chlorophyll, remote sensing reflectance, and fluorescence line height. This method could be used as a gap-filling technique for the future Ocean Color Instrument (OCI) onboard upcoming NASA's Plankton, Aerosol Cloud, ocean Ecosystem (PACE) satellite to provide additional information for monitoring the health of our global oceans. Additionally, it could be applied to the first NASA and Smithsonian geostationary Tropospheric Emissions: Monitoring of Pollution (TEMPO) spectrometer to better understand diurnal variability in inland and coastal ocean ecology.

Zachary Fasnacht↗
DOE OSTI2023

Tritium Safety: Self-Study Course 11952

Course Overview: Tritium is a radioactive isotope of hydrogen which has characteristics that require workers understand what should be done to work safely and responsibly around it. Tritium is used for defense applications, experimental purposes for general research, and is a byproduct of some of the work that is done at LANL. Practical guidance offered in this training will inform safe handling to minimize negative impacts on personnel, the workspace, and the surrounding environment. This course, Tritium Safety Self-Study (Course 11952), provides information on the physical, chemical, and radioactive properties of tritium; sources of tritium; uses of tritium; biological effects of tritium; radiological control methods for tritium; monitoring methods of tritium; tritium waste minimization and handling; and alarms and proper response to abnormal conditions in a tritium facility. Course Objectives: When you have completed this course, you will be able to: Identify the physical, chemical, and radioactive properties of tritium; Identify the sources of tritium; Identify the uses of tritium; Identify the modes of tritium exposure; Identify the biological effects of tritium; Identify the radiological control methods of tritium; Identify methods used to monitor for tritium; Identify tritium waste minimization and handling techniques; Identify proper response to abnormal conditions in tritium facilities.

61 RADIATION PROTECTION AND DOSIMETRY↗
NASA NTRS2004

The Genesis Mission Solar Wind Collection: Solar-Wind Statistics over the Period of Collection

The NASA Genesis spacecraft was launched August 8, 2001 on a mission to collect samples of solar wind for 2 years and return them to earth September 8, 2004. Detailed analyses of the solar wind ions implanted into high-purity collection substrates will be carried out using various mass spectrometry techniques. These analyses are expected to determine key isotopic ratios and elemental abundances in the solar wind, and by extension, in the solar photosphere. Further, the photospheric composition is thought to be representative of the solar nebula with a few exceptions, so that the Genesis mission will provide a baseline for the average solar nebula composition with which to compare present-day compositions of planets, meteorites, and asteroids. The collection of solar wind samples is almost complete. Collection began for most substrates in early December, 2001, and is scheduled to be complete on April 2 of this year. It is critical to understand the solar-wind conditions during the collection phase of the mission. For this reason, plasma ion and electron spectrometers are continuously monitoring the solar wind proton density, velocity, temperature, the alpha/proton ratio, and angular distribution of suprathermal electrons. Here we report on the solar-wind conditions as observed by these in-situ instruments during the first half of the collection phase of the mission, from December, 2001 to present.

Barraclough, B. L.↗
DOE OSTI2022

4D electrical resistivity tomography for assessing the influence of vegetation and subsurface moisture on railway cutting condition

Instability of slopes, embankments, and cuttings on the railway network is increasingly prevalent globally. Monitoring vulnerable infrastructure aids in geotechnical asset management, and improvements to transport safety and efficiency. Here, we examine the use of a novel, near-real-time Electrical Resistivity Tomography (ERT) monitoring system for assessing the stability of a railway cutting in Leicestershire, United Kingdom. In 2015, an ERT monitoring system was installed across a relict landslide (grassed) and an area of more stable ground on either side (wooded), to monitor changes in electrical resistivity through time and space, and to assess the influence of different types of vegetation on the stability of transportation infrastructure. Two years of 4-Dimensional ERT monitoring results are presented here, and petrophysical relationships developed in the laboratory are applied to calibrate the resistivity models in order to provide an insight into hydrogeological pathways within a railway cutting. The influence of vegetation type on subsurface moisture pathways and on slope stability is also assessed – here we find that seasonal subsurface changes in moisture content and soil suction are exacerbated by the presence of trees (wooded area). This results in shrink-swell behaviour of the clays comprising the railway cutting, resulting in fissuring and a reduction in shear strength, leading to instability. As such, it is proposed that on slopes comprised of expansive soils, grassed slopes are beneficial for stability. Insights into the use of 4-D ERT for monitoring railway infrastructure gained from this study may be applied to the monitoring of critical geotechnical assets elsewhere.

58 GEOSCIENCES↗
NASA NTRS1979

Geos 3 wave height measurements - An assessment during high sea state conditions in the North Atlantic

The sea state in the North Atlantic Ocean has been monitored in February, 1977 to obtain data for verification of Geos 3 radio altimeter wave form data. The altimeter sea state data were found to be in good agreement with in situ sea state measurements and with aircraft remote sensing measurements of wave height. The average difference between the supporting data and Geos 3 was 0.34 m, and the standard deviation 0.61 m. Contour maps of sea state constructed for large regions of the earth's oceans on the basis of Geos 3 altimeter measurements exhibited systematic differences from operationally available computerized maps. It is thought that the underestimation of significant wave height maxima in the operational maps and the underestimation of the speed of movement of oceanic cyclones may be due to basic errors in the output of atmospheric primitive-equation models. Because of the narrow swath width of the Geos-3 sensor, data from several satellite orbits must be combined to construct contour maps, leading to low values of significant wave heights.

Parsons, C. L.↗
NASA NTRS1995

Fiber-Optic Based Compact Gas Leak Detection System

A propellant leak detection system based on Raman scattering principles is introduced. The proposed system is flexible and versatile as the result of the use of optical fibers. It is shown that multiple species can be monitored simultaneously. In this paper oxygen, nitrogen, carbon monoxide, and hydrogen are detected and monitored. The current detection sensitivity for both hydrogen and carbon monoxide is 1% partial pressure at ambient conditions. The sensitivity for oxygen and nitrogen is 0.5% partial pressure. The response time to changes in species concentration is three minutes. This system can be used to monitor multiple species at several locations.

deGroot, Wim A.↗
NASA NTRS2004

Health Sensing Functions in Thermal Barrier Coatings Incorporating Rare-Earth-Doped Luminescent Sublayers

Great effort has been directed towards developing techniques to monitor the health of thermal barrier coatings (TBCs) that would detect the approach of safety-threatening conditions. An unconventional approach is presented here where health sensing functionality is integrated into the TBC itself by the incorporation of rare-earth-doped luminescent sublayers to monitor erosion as well as whether the TBC is maintaining the underlying substrate at a sufficiently low temperature. Erosion indication is demonstrated in electron-beam physical vapor deposited (EB-PVD) TBCs consisting of 7wt% yttria-stabilized zirconia (7YSZ) with europium-doped and terbium-doped sublayers. Multiple ingot deposition produced sharp boundaries between the doped sublayers without interrupting the columnar growth of the TBC. The TBC-coated specimens were subjected to alumina particle jet erosion, and the erosion depth was then indicated under ultraviolet illumination that excited easily visible luminescence characteristic of sublayer that was exposed by erosion. In addition, temperature measurements from a bottom-lying europium-doped sublayer in a TBC produced by multiple ingot EB-PVD were accomplished by measuring the temperature-dependent decay time from the 606 nm wavelength emission excited in that sublayer with a 532 nm wavelength laser that was selected for its close match to one of the europium excitation wavelengths as well as being at a wavelength where the TBC is relatively transparent. It is proposed the low dopant levels and absence of interruption of the TBC columnar growth allow the addition of the erosion and temperature sensing functions with minimal effects on TBC performance.

Eldridge, J. I.↗
NASA NTRS2007

Neural Net Safety Monitor Design

The National Aeronautics and Space Administration (NASA) at the Dryden Flight Research Center (DFRC) has been conducting flight-test research using an F-15 aircraft (figure 1). This aircraft has been specially modified to interface a neural net (NN) controller as part of a single-string Airborne Research Test System (ARTS) computer with the existing quad-redundant flight control system (FCC) shown in figure 2. The NN commands are passed to FCC channels 2 and 4 and are cross channel data linked (CCDL) to the other computers as shown. Numerous types of fault-detection monitors exist in the FCC when the NN mode is engaged; these monitors would cause an automatic disengagement of the NN in the event of a triggering fault. Unfortunately, these monitors still may not prevent a possible NN hard-over command from coming through to the control laws. Therefore, an additional and unique safety monitor was designed for a single-string source that allows authority at maximum actuator rates but protects the pilot and structural loads against excessive g-limits in the case of a NN hard-over command input. This additional monitor resides in the FCCs and is executed before the control laws are computed. This presentation describes a floating limiter (FL) concept1 that was developed and successfully test-flown for this program (figure 3). The FL computes the rate of change of the NN commands that are input to the FCC from the ARTS. A window is created with upper and lower boundaries, which is constantly floating and trying to stay centered as the NN command rates are changing. The limiter works by only allowing the window to move at a much slower rate than those of the NN commands. Anywhere within the window, however, full rates are allowed. If a rate persists in one direction, it will eventually hit the boundary and be rate-limited to the floating limiter rate. When this happens, a persistent counter begins and after a limit is reached, a NN disengage command is generated. The tunable metrics for the FL are (1) window size, (2) drift rate, and (3) persistence counter. Ultimate range limits are also included in case the NN command should drift slowly to a limit value that would cause the FL to be defeated. The FL has proven to work as intended. Both high-g transients and excessive structural loads are controlled with NN hard-over commands. This presentation discusses the FL design features and presents test cases. Simulation runs are included to illustrate the dramatic improvement made to the control of NN hard-over effects. A mission control room display from a flight playback is presented to illustrate the neural net fault display representation. The FL is very adaptable to various requirements and is independent of flight condition. It should be considered as a cost-effective safety monitor to control single-string inputs in general.

Larson, Richard R.↗
NASA NTRS2009

Implementation of an Adaptive Controller System from Concept to Flight Test

The National Aeronautics and Space Administration (NASA) at the Dryden Flight Research Center (DFRC) has been conducting flight-test research using an F-15 aircraft (figure 1). This aircraft has been specially modified to interface a neural net (NN) controller as part of a single-string Airborne Research Test System (ARTS) computer with the existing quad-redundant flight control system (FCC) shown in figure 2. The NN commands are passed to FCC channels 2 and 4 and are cross channel data linked (CCDL) to the other computers as shown. Numerous types of fault-detection monitors exist in the FCC when the NN mode is engaged; these monitors would cause an automatic disengagement of the NN in the event of a triggering fault. Unfortunately, these monitors still may not prevent a possible NN hard-over command from coming through to the control laws. Therefore, an additional and unique safety monitor was designed for a single-string source that allows authority at maximum actuator rates but protects the pilot and structural loads against excessive g-limits in the case of a NN hard-over command input. This additional monitor resides in the FCCs and is executed before the control laws are computed. This presentation describes a "floating limiter" (FL) concept that was developed and successfully test-flown for this program (figure 3). The FL computes the rate of change of the NN commands that are input to the FCC from the ARTS. A window is created with upper and lower boundaries, which is constantly "floating" and trying to stay centered as the NN command rates are changing. The limiter works by only allowing the window to move at a much slower rate than those of the NN commands. Anywhere within the window, however, full rates are allowed. If a rate persists in one direction, it will eventually "hit" the boundary and be rate-limited to the floating limiter rate. When this happens, a persistent counter begins and after a limit is reached, a NN disengage command is generated. The tunable metrics for the FL are (1) window size, (2) drift rate, and (3) persistence counter. Ultimate range limits are also included in case the NN command should drift slowly to a limit value that would cause the FL to be defeated. The FL has proven to work as intended. Both high-g transients and excessive structural loads are controlled with NN hard-over commands. This presentation discusses the FL design features and presents test cases. Simulation runs are included to illustrate the dramatic improvement made to the control of NN hard-over effects. A mission control room display from a flight playback is presented to illustrate the neural net fault display representation. The FL is very adaptable to various requirements and is independent of flight condition. It should be considered as a cost-effective safety monitor to control single-string inputs in general.

Larson, Richard R.↗
DOE OSTI2025

Hyperspectral segmentation of plants in fabricated ecosystems

Hyperspectral imaging provides a powerful tool for analyzing above-ground plant characteristics in fabricated ecosystems, offering rich spectral information across diverse wavelengths. This study presents an efficient workflow for hyperspectral data segmentation and subsequent data analytics, minimizing the need for user annotation through the use of ensembles of sparse mixed scale convolution neural networks. The segmentation process leverages the diversity of ensembles to achieve high accuracy with minimal labeled data, reducing labor-intensive annotation efforts. To further enhance robustness, we incorporate image alignment techniques to address spatial variability in the dataset. Downstream analysis focuses on using the segmented data for processing spectral data, enabling monitoring of plant health. This approach provides a scalable solution for spectral segmentation, and facilitates actionable insights into plant conditions in complex, controlled environments. Our results demonstrate the utility of combining advanced machine learning techniques with hyperspectral analytics for high-throughput plant monitoring.

Zwart, Petrus H.↗