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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

A novel approach to increasing cocaine detection confidence utilizing ion mobility spectrometry

When a positive detection of a narcotic occurs during the search of a vessel, a decision has to be made whether further intensive search is warranted. In terms of unwarranted delays of vessels and possible property damage, the accuracy of the analytical determination is very important. Analytical accuracy becomes critical when the data may be used in court actions as evidence. For this purpose, the U.S. Coast Guard has been investigating several confirmatory ion mobility spectrometry (IMS) field methods for the detection and identification of cocaine. This paper presents the findings of our investigations on the use of catalytic pyrolysis and base hydrolysis as confirmatory methods. The catalytic effects of various metals on the pyrolysis reaction are reported. In addition, the effects of several different ion mobility spectrometer sample transfer mediums and varying laboratory conditions on the base hydrolysis of the cocaine molecule are also be reported.

Jadamec, J. Richard↗
NASA NTRS1994

Multiplex approach to the photometric detection of planets

If the hypothesis is correct that most solar-like stars have planetary systems and have planets in inner orbits, then approximately 1% of these stars should have planets with orbital planes close enough to our line of sight to show transits. To get a statistically significant estimate of the fraction of stars that have planets in inner orbits, it is necessary to monitor thousands of stars continuously for a period of several years. To accomplish this requires the use of a multi-channel photometer system. We present here several multi-channel methods that have been used for ground-based observations and a concept for applying multi-channel photometry to the detection of numerous Earth-sized planets.

Borucki, William↗
NASA NTRS2006

A Resonant Synchronous Vibration Based Approach for Rotor Imbalance Detection

This paper presents a methodology of detecting rotor imbalances, such as mass imbalance and crack-induced imbalance, using shaft synchronous vibrations. An iterative scheme is developed to identify parameters from measured synchronous vibration data. A detection system is integrated by using state-of-the-art commercial analysis equipment. A laboratory rotor test rig is used to verify the system integration and algorithm validation. A real engine test has been carried out and the results are reported.

Luo, Huangeng↗
NASA NTRS2013

Millimeter-Wave Localizers for Aircraft-to-Aircraft Approach Navigation

Aerial refueling technology for both manned and unmanned aircraft is critical for operations where extended aircraft flight time is required. Existing refueling assets are typically manned aircraft, which couple to a second aircraft through the use of a refueling boom. Alignment and mating of the two aircraft continues to rely on human control with use of high-resolution cameras. With the recent advances in unmanned aircraft, it would be highly advantageous to remove/reduce human control from the refueling process, simplifying the amount of remote mission management and enabling new operational scenarios. Existing aerial refueling uses a camera, making it non-autonomous and prone to human error. Existing commercial localizer technology has proven robust and reliable, but not suited for aircraft-to-aircraft approaches like in aerial refueling scenarios since the resolution is too coarse (approximately one meter). A localizer approach system for aircraft-to-aircraft docking can be constructed using the same modulation with a millimeterwave carrier to provide high resolution. One technology used to remotely align commercial aircraft on approach to a runway are ILS (instrument landing systems). ILS have been in service within the U.S. for almost 50 years. In a commercial ILS, two partially overlapping beams of UHF (109 to 126 MHz) are broadcast from an antenna array so that their overlapping region defines the centerline of the runway. This is called a localizer system and is responsible for horizontal alignment of the approach. One beam is modulated with a 150-Hz tone, while the other with a 90-Hz tone. Through comparison of the modulation depths of both tones, an autopilot system aligns the approaching aircraft with the runway centerline. A similar system called a glide-slope (GS) exists in the 320-to-330MHz band for vertical alignment of the approach. While this technology has been proven reliable for millions of commercial flights annually, its UHF nature limits its ability to operate beyond the 1-to-2-meter precisions associated with commercial runway width. A prototype ILS-type system operates at millimeter-wave frequencies to provide automatic and robust approach control for aerial refueling. The system allows for the coupling process to remain completely autonomous, as a boom operator is no longer required. Operating beyond 100 GHz provides enough resolution and a narrow enough beamwidth that an approach corridor of centimeter scales can be maintained. Two modules were used to accomplish this task. The first module is a localizer/glide-slope module that can be fitted on a refueling aircraft. This module provides the navigation beams for aligning the approaching aircraft. The second module is navigational receiver fitted onto the approaching aircraft to be re fueled that can detect the approach beams. Since unmanned aircraft have a limited payload size and limited electrical power, the receiver portion was implemented in CMOS (complementary metal oxide semiconductor) technology based on a super-regenerative receiver (SRR) architecture. The SRR achieves mW-level power consumption and chip sizes less than l mm2. While super-regenerative techniques have small bandwidths that limit use in communication systems, their advantages of high sensitivity, low complexity, and low power make them ideal in this situation where modulating tones of less than 1 kHz are used.

Tang, Adrian J.↗
NASA NTRSDate not supplied

Autonomous Spacecraft Inspection with Free-Flying Drones

This paper describes a proof-of-concept mission demonstrating a multi-agent system performing visual inspection of damage sustained by a spacecraft. Free-flying satellites, simulated by unmanned aerial vehicles (UAVs), autonomously fly around a mock space module maximizing the search space for damage detection. The free-flyers are responsible for independently coordinating their flights to avoid collision with the space module and each other, while executing mission tasks. Damage analysis on the surface of the mock space module is performed in real-time using video from each free-flyer. Three-dimensional modeling is deployed offline to supplement and improve damage detection. This approach demonstrates the feasibility of deploying real space systems for damage detection, where 2D analysis can quickly determine region of interest and 3D visualization can produce a human-navigable virtual environment with depth perspective for further investigation.

unmanned aerial vehicle (UAV)↗
NASA NTRS1996

Detection of Structural Abnormalities Using Neural Nets

This paper describes a feed-forward neural net approach for detection of abnormal system behavior based upon sensor data analyses. A new dynamical invariant representing structural parameters of the system is introduced in such a way that any structural abnormalities in the system behavior are detected from the corresponding changes to the invariant.

abnormal system behavior system behavior sensor da↗
NASA NTRS2001

Operational Cloud Detection in GEOS Imagery

The bispectral spatial coherence approach for the detection and masking of clouds is revisited with modifications for operational applications to Geostationary Operational Environmental Satellite (GOES) Imager and Sounder data. The approach applies an edge detection algorithm to a "difference" image to identify the edges or contours of the clouds. The difference image is generated as the difference between the 3.9 and 11 micrometer channels of the GOES sensors. This difference image better highlights cloud edges than either image alone and draws upon the emissivity differences in the various channels. The cloud contours are "filled-in" by referencing the thermal gradients in the 11-micrometer channel or difference image associated with the cloud edge. This paper and associate poster will present a preliminary validation of the bispectral spatial coherence approach and will compare the cloud masks generated with this approach to the National Oceanic and Atmospheric Administration/National Environmental Satellite, Data, and Information Service (NOAA/NESDIS) operational cloud products.

Jedlovec, Gary J.↗
NASA NTRS1990

Photon detection with parallel asynchronous processing

An approach to photon detection with a parallel asynchronous signal processor is described. The visible or IR photon-detection capability of the silicon p(+)-n-n(+) detectors and the parallel asynchronous processing are addressed separately. This approach would permit an independent analog processing channel to be dedicated to every pixel. A laminar architecture consisting of a stack of planar arrays of the devices would form a 2D array processor with a 2D array of inputs located directly behind a focal-plane detector array. A 2D image data stream would propagate in neuronlike asynchronous pulse-coded form through the laminar processor. Such systems can integrate image acquisition and image processing. Acquisition and processing would be performed concurrently as in natural vision systems. The possibility of multispectral image processing is addressed.

Coon, D. D.↗
NASA NTRS2005

Aircraft Fault Detection and Classification Using Multi-Level Immune Learning Detection

This work is an extension of a recently developed software tool called MILD (Multi-level Immune Learning Detection), which implements a negative selection algorithm for anomaly and fault detection that is inspired by the human immune system. The immunity-based approach can detect a broad spectrum of known and unforeseen faults. We extend MILD by applying a neural network classifier to identify the pattern of fault detectors that are activated during fault detection. Consequently, MILD now performs fault detection and identification of the system under investigation. This paper describes the application of MILD to detect and classify faults of a generic transport aircraft augmented with an intelligent flight controller. The intelligent control architecture is designed to accommodate faults without the need to explicitly identify them. Adding knowledge about the existence and type of a fault will improve the handling qualities of a degraded aircraft and impact tactical and strategic maneuvering decisions. In addition, providing fault information to the pilot is important for maintaining situational awareness so that he can avoid performing an action that might lead to unexpected behavior - e.g., an action that exceeds the remaining control authority of the damaged aircraft. We discuss the detection and classification results of simulated failures of the aircraft's control system and show that MILD is effective at determining the problem with low false alarm and misclassification rates.

Wong, Derek↗
NASA NTRS1975

The analysis of the pilot's cognitive and decision processes

Articles are presented on pilot performance in zero-visibility precision approach, failure detection by pilots during automatic landing, experiments in pilot decision-making during simulated low visibility approaches, a multinomial maximum likelihood program, and a random search algorithm for laboratory computers. Other topics discussed include detection of system failures in multi-axis tasks and changes in pilot workload during an instrument landing.

Curry, R. E.↗
NASA NTRS1992

The ionosphere as a gamma ray burst detector

Unlike all man made detectors, which are only sensitive to relative narrow regions of the electromagnetic spectrum, the ionosphere is practically a perfect detector for high energy radiation because it absorbs all radiation from the far-ultraviolet to the higher energy gamma-rays. Therefore, it may be possible to employ the terrestrial atmosphere as a detector of high energy celestial photons. As early as the 1940's solar flares were detected by the disturbance they caused to the ionosphere. The VLF (3 - 30 kHz) approach for detecting ionospheric disturbances is based on the following physical circumstance: celestial high energy radiation ionizes the atoms of the earth's ionosphere leading to the production of free electrons. These free electrons influence the propagation of electromagnetic waves. By studying the phase and amplitude changes of VLF radio wave propagating in the earth-ionosphere waveguide, it was hoped to ascertain the electron density in these regions and draw conclusions about the celestial radiation which caused them. To detect gamma-ray bursts, two conditions for the optimal detection are: (1) large zenith angle; and (2) alignment of burst and propagation path.

Mcgruder, Charles H., III↗
NASA NTRSDate not supplied

Transition Measurements on the SWiFT Model in the National Transonic Facility

Boundary layer transition locations on the Swept Wing Flow Test (SWiFT) Hybrid Wing Body model were measured in the National Transonic Facility (NTF) at the NASA Langley Research Center using several different methods. These methods include sublimating chemical flow visualization for a limited number of low Reynolds number conditions, as well as mean static pressure and dynamic pressure measurements. Results are presented for a range of conditions in the NTF, demonstrating Mach and Reynolds number effects. The transition front locations obtained from the different techniques agree well. A variation of the static pressure transition detection method is described in which continuous angle of attack polars are performed. This approach enables detection of the transition front at more challenging (high Reynolds number) conditions than is possible with sparser data from pitch-pause angle-of-attack polars. The trip dot effectiveness is also verified using all of the available diagnostics. Additionally, low Reynolds number results are compared with those acquired on the same model at the Aircraft Research Association (ARA) facility, and these results show good agreement overall, suggesting similar freestream flow quality conditions of the two facilities.

National Transonic Facility↗
NASA NTRSDate not supplied

Transition Measurements on the SWiFT Model in the National Transonic Facility

Boundary layer transition locations on the Swept Wing Flow Test (SWiFT) Hybrid Wing Body model were measured in the National Transonic Facility (NTF) at the NASA Langley Research Center using several different methods. These methods include sublimating chemical flow visualization for a limited number of low Reynolds number conditions, as well as mean static pressure and dynamic pressure measurements. Results are presented for a range of conditions in the NTF, demonstrating Mach and Reynolds number effects. The transition front locations obtained from the different techniques agree well. A variation of the static pressure transition detection method is described in which continuous angle of attack polars are performed. This approach enables detection of the transition front at more challenging (high Reynolds number) conditions than is possible with sparser data from pitch-pause angle-of-attack polars. The trip dot effectiveness is also verified using all of the available diagnostics. Additionally, low Reynolds number results are compared with those acquired on the same model at the Aircraft Research Association (ARA) facility, and these results show good agreement overall, suggesting similar freestream flow quality conditions of the two facilities.

National Transonic Facility↗
NASA NTRSDate not supplied

Capturing Complex Multivariate Time Series Interactions to Detect High-Risk Adverse Events During Flight

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗
NASA NTRS2002

Low-Cost Evaluation of EO-1 Hyperion and ALI for Detection and Biophysical Characterization of Forest Logging in Amazonia (NCC5-481)

Major uncertainties exist regarding the rate and intensity of logging in tropical forests worldwide: these uncertainties severely limit economic, ecological, and biogeochemical analyses of these regions. Recent sawmill surveys in the Amazon region of Brazil show that the area logged is nearly equal to total area deforested annually, but conversion of survey data to forest area, forest structural damage, and biomass estimates requires multiple assumptions about logging practices. Remote sensing could provide an independent means to monitor logging activity and to estimate the biophysical consequences of this land use. Previous studies have demonstrated that the detection of logging in Amazon forests is difficult and no studies have developed either the quantitative physical basis or remote sensing approaches needed to estimate the effects of various logging regimes on forest structure. A major reason for these limitations has been a lack of sufficient, well-calibrated optical satellite data, which in turn, has impeded the development and use of physically-based, quantitative approaches for detection and structural characterization of forest logging regimes. We propose to use data from the EO-1 Hyperion imaging spectrometer to greatly increase our ability to estimate the presence and structural attributes of selective logging in the Amazon Basin. Our approach is based on four "biogeophysical indicators" not yet derived simultaneously from any satellite sensor: 1) green canopy leaf area index; 2) degree of shadowing; 3) presence of exposed soil and; 4) non-photosynthetic vegetation material. Airborne, field and modeling studies have shown that the optical reflectance continuum (400-2500 nm) contains sufficient information to derive estimates of each of these indicators. Our ongoing studies in the eastern Amazon basin also suggest that these four indicators are sensitive to logging intensity. Satellite-based estimates of these indicators should provide a means to quantify both the presence and degree of structural disturbance caused by various logging regimes. Our quantitative assessment of Hyperion hyperspectral and ALI multi-spectral data for the detection and structural characterization of selective logging in Amazonia will benefit from data collected through an ongoing project run by the Tropical Forest Foundation, within which we have developed a study of the canopy and landscape biophysics of conventional and reduced-impact logging. We will add to our base of forest structural information in concert with an EO-1 overpass. Using a photon transport model inversion technique that accounts for non-linear mixing of the four biogeophysical indicators, we will estimate these parameters across a gradient of selective logging intensity provided by conventional and reduced impact logging sites. We will also compare our physical ly-based approach to both conventional (e.g., NDVI) and novel (e.g., SWIR-channel) vegetation indices as well as to linear mixture modeling methods. We will cross-compare these approaches using Hyperion and ALI imagers to determine the strengths and limitations of these two sensors for applications of forest biophysics. This effort will yield the first physical ly-based, quantitative analysis of the detection and intensity of selective logging in Amazonia, comparing hyperspectral and improved multi-spectral approaches as well as inverse modeling, linear mixture modeling, and vegetation index techniques.

Asner, Gregory P.↗
NASA NTRS2000

Determination of anionic surfactants during wastewater recycling process by ion pair chromatography with suppressed conductivity detection

A direct approach utilizing ion pairing reversed-phase chromatography coupled with suppressed conductivity detection was developed to monitor biodegradation of anionic surfactants during wastewater recycling through hydroponic plant growth systems and fixed-film bioreactors. Samples of hydroponic nutrient solution and bioreactor effluent with high concentrations (up to 120 mS electrical conductance) of inorganic ions can be analyzed without pretreatment or interference. The presence of non-ionic surfactants did not significantly affect the analysis. Dynamic linear ranges for tested surfactants [Igepon TC-42, ammonium lauryl sulfate, sodium laureth sulfate and sodium alkyl (C10-C16) ether sulfate] were 2 to approximately 500, 1 to approximately 500, 2.5 to approximately 550 and 3.0 to approximately 630 microg/ml, respectively.

NASA Program Advanced Human Support Technology↗
NASA NTRS1988

The prospects for detecting spectral shifts due to satellite sensor aging

Along with responsivity changes due to sensor aging, there may be concurrent spectral changes. A field-measurement approach for detecting postlaunch spectral changes is described. For illustration, one hypothetical model of change (spectral band shift) is explored through simulation for five satellite sensors. Two different types of natural terrain - vegetation and bare soil - are used as test targets.

Suits, G.↗