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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Classifying Unidentified X-Ray Sources in the Chandra Source Catalog Using A Multiwavelength Machine-Learning Approach

The rapid increase in serendipitous X-ray source detections requires the development of novel approaches to efficiently explore the nature of X-ray sources. If even a fraction of these sources could be reliably classified, it would enable population studies for various astrophysical source types on a much larger scale than currently possible. Classification of large numbers of sources from multiple classes characterized by multiple properties (features) must be done automatically and supervised machine learning (ML) seems to provide the only feasible approach. We perform classification of Chandra Source Catalog version 2.0 (CSCv2) sources to explore the potential of the ML approach and identify various biases, limitations, and bottlenecks that present themselves in these kinds of studies. We establish the framework and present a flexible and expandable Python pipeline, which can be used and improved by others. We also release the training data set of 2941 X-ray sources with confidently established classes. In addition to providing probabilistic classifications of 66,369 CSCv2 sources (21% of the entire CSCv2 catalog), we perform several narrower-focused case studies (high-mass X-ray binary candidates and X-ray sources within the extent of the H.E.S.S. TeV sources) to demonstrate some possible applications of our ML approach. We also discuss future possible modifications of the presented pipeline, which are expected to lead to substantial improvements in classification confidences.

Hui Yang↗
NASA NTRS1993

Experimental evaluation of certification trails using abstract data type validation

Certification trails are a recently introduced and promising approach to fault-detection and fault-tolerance. Recent experimental work reveals many cases in which a certification-trail approach allows for significantly faster program execution time than a basic time-redundancy approach. Algorithms for answer-validation of abstract data types allow a certification trail approach to be used for a wide variety of problems. An attempt to assess the performance of algorithms utilizing certification trails on abstract data types is reported. Specifically, this method was applied to the following problems: heapsort, Hullman tree, shortest path, and skyline. Previous results used certification trails specific to a particular problem and implementation. The approach allows certification trails to be localized to 'data structure modules,' making the use of this technique transparent to the user of such modules.

Wilson, Dwight S.↗
NASA NTRS2000

Kepler Mission: End-to-End System Demonstration

A test facility has been constructed to demonstrate the capability of differential ensemble photometry to detect transits of Earth-size planets orbiting solar-like stars. The main objective is to determine the effects of various noise sources on the capability of a CCD photometer to maintain a system relative precision of 1 x $10^(-5)$ for mv = 12 stars in the presence of system-induced noise sources. The facility includes a simulated star field, fast optics to simulate the telescope, a thinned back-illuminated CCD similar to those to be used on the spacecraft and computers to perform the onboard control, data processing and extraction. The test structure is thermally and mechanically isolated so that each source of noise can be introduced in a controlled fashion and evaluated for its contribution to the total noise budget. The effects of pointing errors or a changing thermal environment are imposed by piezo-electric devices. Transits are injected by heating small wires crossing apertures in the star plate. Signals as small as those from terrestrial-size transits of solar-like stars are introduced to demonstrate that such planets can be detected under realistic noise conditions. Examples of imposing several noise sources and the resulting detectabilities are presented. These show that a differential ensemble photometric approach CCD photometer can readily detect signals associated with Earth-size transits.

Borucki, William↗
NASA NTRS2014

An Efficient, Multi-Layered Crown Delineation Algorithm for Mapping Individual Tree Structure Across Multiple Ecosystems

Deriving individual tree information from discrete return, small footprint LiDAR data may improve forest above ground biomass estimates, and provide tree-level information that is important in many ecological studies. Several crown delineation algorithms have been developed to extract individual tree information from LiDAR point clouds or rasterized canopy height models (CHM), but many of these algorithms have difficulty discriminating between overlapping crowns, and also may fail to detect understory trees. Our approach uses a watershed based delineation of a CHM, which is subsequently refined using the LiDAR point cloud. Individual tree detection was validated with stem mapped field data from the Smithsonian Environmental Research Center (SERC), Maryland, and on a plot and stand level through comparisons of stem density and basal area to delineated metrics at both SERC and a study area in the Sierra Nevada, California. For individual tree detection, the algorithm correctly identified 70% of dominant trees, 58% of co-dominant trees, 35% of intermediate trees and 21% of suppressed trees at SERC. The algorithm had difficulty distinguishing between crowns of small, dense understory trees of approximately the same height. Delineated crown volume alone explained 53% and 84% of the variability in basal area at the SERC and Sierra Nevada sites, respectively. The algorithm produced crown area distributions comparable to diameter at breast height (DBH) size class distributions observed in the field in both study sites. The algorithm detected understory crowns better in the conifer-dominated Sierra Nevada site than in the closed-canopy deciduous site in Maryland. The ability for the algorithm to reproduce both accurate tree size distributions and individual crown geometries in two dissimilar and complex forests suggests great promise for applicability to a wide range of forest systems.

LiDAR↗
NASA NTRS2020

Optically targeted search for gravitational waves emitted by core-collapse supernovae during the first and second observing runs of advanced LIGO and advanced Virgo

We present the results from a search for gravitational-wave transients associated with core-collapse supernovae observed within a source distance of approximately 20 Mpc during the first and second observing runs of Advanced LIGO and Advanced Virgo. No significant gravitational-wave candidate was detected. We report the detection efficiencies as a function of the distance for waveforms derived from multidimensional numerical simulations and phenomenological extreme emission models. The sources with neutrino-driven explosions are detectable at the distances approaching 5 kpc, and for magnetorotationally driven explosions the distances are up to 54 kpc. However, waveforms for extreme emission models are detectable up to 28 Mpc. For the first time, the gravitational-wave data enabled us to exclude part of the parameter spaces of two extreme emission models with confidence up to 83%, limited by coincident data coverage. Besides, using ad hoc harmonic signals windowed with Gaussian envelopes, we constrained the gravitational-wave energy emitted during core collapse at the levels of 4.27 × 10^(−4) Mꙩc^(2) and 1.28 × 10^(−1) Mꙩc^(2) for emissions at 235 and 1304 Hz, respectively. These constraints are 2 orders of magnitude more stringent than previously derived in the corresponding analysis using initial LIGO, initial Virgo, and GEO 600 data.

B. P. Abbott↗
NASA NTRS2004

Immunity-Based Aircraft Fault Detection System

In the study reported in this paper, we have developed and applied an Artificial Immune System (AIS) algorithm for aircraft fault detection, as an extension to a previous work on intelligent flight control (IFC). Though the prior studies had established the benefits of IFC, one area of weakness that needed to be strengthened was the control dead band induced by commanding a failed surface. Since the IFC approach uses fault accommodation with no detection, the dead band, although it reduces over time due to learning, is present and causes degradation in handling qualities. If the failure can be identified, this dead band can be further A ed to ensure rapid fault accommodation and better handling qualities. The paper describes the application of an immunity-based approach that can detect a broad spectrum of known and unforeseen failures. The approach incorporates the knowledge of the normal operational behavior of the aircraft from sensory data, and probabilistically generates a set of pattern detectors that can detect any abnormalities (including faults) in the behavior pattern indicating unsafe in-flight operation. We developed a tool called MILD (Multi-level Immune Learning Detection) based on a real-valued negative selection algorithm that can generate a small number of specialized detectors (as signatures of known failure conditions) and a larger set of generalized detectors for unknown (or possible) fault conditions. Once the fault is detected and identified, an adaptive control system would use this detection information to stabilize the aircraft by utilizing available resources (control surfaces). We experimented with data sets collected under normal and various simulated failure conditions using a piloted motion-base simulation facility. The reported results are from a collection of test cases that reflect the performance of the proposed immunity-based fault detection algorithm.

Dasgupta, D.↗
NASA NTRS2020

In-Flight Detection of Vibration Anomalies in Unmanned Aerial Vehicles

Owing to the frequency of occurrence and high risk associated with bearings, identification and characterization of bearing faults in motors via nondestructive evaluation (NDE) methods have been studied extensively, amongst which vibration analysis has been found to be a promising technique for early diagnosis of anomalies. However, a majority of the existing techniques rely on vibration sensors attached onto or in close proximity to the motor in order to collect signals with a relatively high SNR. Due to weight and space restrictions, these techniques cannot be used in unmanned aerial vehicles (UAVs), especially during flight operations since accelerometers cannot be attached onto motors in small UAVs. Small UAVs are often subjected to vibrational disturbances caused by multiple factors such as weather turbulence, propeller imbalance or bearing faults. Such anomalies may not only pose risks to UAV's internal circuitry, components or payload, they may also generate undesirable noise level particularly for UAVs expected to fly in low-altitudes or urban canyon. This paper presents a detailed discussion of challenges in in-flight detection of bearing failure in UAVs using existing approaches and offers potential solutions to detect overall vibration anomalies in small UAV operations based on IMU data.

Portia Banerjee↗
NASA NTRSDate not supplied

VSLAM and Coplanar POSIT for Advanced Air Mobility Approach and Landing

Advanced Air Mobility (AAM) aircraft have many challenges for landing accurately and safely in urban, suburban, and rural environments. Localization in large and open rural environments could utilize GPS, but AAM aircraft in urban environments will encounter GPS degradation. Another challenge involves flight operation time, i.e., flying during the day or at night. There are different types of guidelines and landmarks at runways, heliports, and vertiports for daytime and nighttime applications. Tailoring feature detection methods for AAM approach and landing during the day and night pose different issues and challenges. It is easier to detect edges, lines, and other runway markers during the day than at night. Conversely, it is easier to detect landing light configurations and patterns at nighttime than daytime. Consequently, utilizing the same feature detector for daytime and nighttime operations may not be feasible. This paper focuses on vision-based precision approach and landing (PAL) and builds on previous work by comparing ORB SLAM, custom VSLAM, and coplanar pose from orthography and scaling with iterations (POSIT) for daytime and nighttime operations. Implementing high fidelity simulations with computer graphics and extracting video frames from flight test data provide promising results for AAM PAL applications.

Evan Kawamura↗
NASA NTRS2011

PMA-PhyloChip DNA Microarray to Elucidate Viable Microbial Community Structure

Since the Viking missions in the mid-1970s, traditional culture-based methods have been used for microbial enumeration by various NASA programs. Viable microbes are of particular concern for spacecraft cleanliness, for forward contamination of extraterrestrial bodies (proliferation of microbes), and for crew health/safety (viable pathogenic microbes). However, a "true" estimation of viable microbial population and differentiation from their dead cells using the most sensitive molecular methods is a challenge, because of the stability of DNA from dead cells. The goal of this research is to evaluate a rapid and sensitive microbial detection concept that will selectively estimate viable microbes. Nucleic acid amplification approaches such as the polymerase chain reaction (PCR) have shown promise for reducing time to detection for a wide range of applications. The proposed method is based on the use of a fluorescent DNA intercalating agent, propidium monoazide (PMA), which can only penetrate the membrane of dead cells. The PMA-quenched reaction mixtures can be screened, where only the DNA from live cells will be available for subsequent PCR reaction and microarray detection, and be identified as part of the viable microbial community. An additional advantage of the proposed rapid method is that it will detect viable microbes and differentiate from dead cells in only a few hours, as opposed to less comprehensive culture-based assays, which take days to complete. This novel combination approach is called the PMA-Microarray method. DNA intercalating agents such as PMA have previously been used to selectively distinguish between viable and dead bacterial cells. Once in the cell, the dye intercalates with the DNA and, upon photolysis under visible light, produces stable DNA adducts. DNA cross-linked in this way is unavailable for PCR. Environmental samples suspected of containing a mixture of live and dead microbial cells/spores will be treated with PMA, and then incubated in the dark. Thereafter, the sample is exposed to visible light for five minutes, so that the DNA from dead cells will be cross-linked. Following this PMA treatment step, the sample is concentrated by centrifugation and washed (to remove excessive PMA) before DNA is extracted. The 16S rRNA gene fragments will be amplified by PCR to screen the total microbial community using PhyloChip DNA microarray analysis. This approach will detect only the viable microbial community since the PMA intercalated DNA from dead cells would be unavailable for PCR amplification. The total detection time including PCR reaction for low biomass samples will be a few hours. Numerous markets may use this technology. The food industry uses spore detection to validate new alternative food processing technologies, sterility, and quality. Pharmaceutical and medical equipment companies also detect spores as a marker for sterility. This system can be used for validating sterilization processes, water treatment systems, and in various public health and homeland security applications.

Venkateswaran, Kasthuri J.↗
NASA NTRS2014

An Integrated Architecture for Aircraft Engine Performance Monitoring and Fault Diagnostics: Engine Test Results

This paper presents a model-based architecture for performance trend monitoring and gas path fault diagnostics designed for analyzing streaming transient aircraft engine measurement data. The technique analyzes residuals between sensed engine outputs and model predicted outputs for fault detection and isolation purposes. Diagnostic results from the application of the approach to test data acquired from an aircraft turbofan engine are presented. The approach is found to avoid false alarms when presented nominal fault-free data. Additionally, the approach is found to successfully detect and isolate gas path seeded-faults under steady-state operating scenarios although some fault misclassifications are noted during engine transients. Recommendations for follow-on maturation and evaluation of the technique are also presented.

propulsion system performance↗
NASA NTRS2014

An Integrated Architecture for Aircraft Engine Performance Monitoring and Fault Diagnostics: Engine Test Results

This paper presents a model-based architecture for performance trend monitoring and gas path fault diagnostics designed for analyzing streaming transient aircraft engine measurement data. The technique analyzes residuals between sensed engine outputs and model predicted outputs for fault detection and isolation purposes. Diagnostic results from the application of the approach to test data acquired from an aircraft turbofan engine are presented. The approach is found to avoid false alarms when presented nominal fault-free data. Additionally, the approach is found to successfully detect and isolate gas path seeded-faults under steady-state operating scenarios although some fault misclassifications are noted during engine transients. Recommendations for follow-on maturation and evaluation of the technique are also presented.

propulsion system performance↗
NASA NTRS2015

An Integrated Architecture for Aircraft Engine Performance Monitoring and Fault Diagnostics: Engine Test Results

This paper presents a model-based architecture for performance trend monitoring and gas path fault diagnostics designed for analyzing streaming transient aircraft engine measurement data. The technique analyzes residuals between sensed engine outputs and model predicted outputs for fault detection and isolation purposes. Diagnostic results from the application of the approach to test data acquired from an aircraft turbofan engine are presented. The approach is found to avoid false alarms when presented nominal fault-free data. Additionally, the approach is found to successfully detect and isolate gas path seeded-faults under steady-state operating scenarios although some fault misclassifications are noted during engine transients. Recommendations for follow-on maturation and evaluation of the technique are also presented.

systems health monitoring↗
NASA NTRS2003

A new relative referencing method for crop monitoring using chlorophyll fluorescence

The measurement of plant chlorophyll fluorescence has been used for many years as a method to monitor a plant's health status. These types of methods have been mostly relegated to the laboratory. The newly developed Relative Referencing Method allows for the measurement of chlorophyll fluorescence under artificial lighting conditions. The fluorescence signal can be determined by first taking a reference signal measurement, then a second measurement with an additional fluorescence excitation source. The first signal can then be subtracted from the second and the plant's chlorophyll fluorescence due to the second lighting source can be determined. With this simple approach, a photosynthesizing plant can be monitored to detect signs of water stress. Using this approach experiments on tomato plants have shown that it was possible to detect water stress, while the plants were continuously illuminated by fluorescent lamps. This method is a promising tool for the remote monitoring of crops grown in a CELSS-type application. Published by Elsevier Science Ltd on behalf of COSPAR.

Plant Physiology↗
NASA NTRS2006

Testing the TPF Interferometry Approach before Launch

One way to directly detect nearby extra-solar planets is via their thermal infrared emission, and with this goal in mind, both NASA and ESA are investigating cryogenic infrared interferometers. Common to both agencies' approaches to faint off-axis source detection near bright stars is the use of a rotating nulling interferometer, such as the Terrestrial Planet Finder interferometer (TPF-I), or Darwin. In this approach, the central star is nulled, while the emission from off-axis sources is transmitted and modulated by the rotation of the off-axis fringes. Because of the high contrasts involved, and the novelty of the measurement technique, it is essential to gain experience with this technique before launch. Here we describe a simple ground-based experiment that can test the essential aspects of the TPF signal measurement and image reconstruction approaches by generating a rotating interferometric baseline within the pupil of a large singleaperture telescope. This approach can mimic potential space-based interferometric configurations, and allow the extraction of signals from off-axis sources using the same algorithms proposed for the space-based missions. This approach should thus allow for testing of the applicability of proposed signal extraction algorithms for the detection of single and multiple near-neighbor companions...

interferometry↗
NASA NTRSDate not supplied

VSLAM and Vision-based Approach and Landing for Advanced Air Mobility

Advanced Air Mobility (AAM) aircraft have many challenges in landing accurately and safely in urban, suburban, and rural environments. Localization in large and open rural environments could utilize GPS, but AAM aircraft in urban environments will encounter GPS degradation. Another challenge involves flight operation time, i.e., flying during the day or at night. There are different guidelines, landmarks, and landing light configurations at runways, heliports, and vertiports for daytime and nighttime applications. Tailoring feature detection methods for AAM approach and landing during the day and night pose different issues and challenges. It is easier to detect edges, lines, and other runway markers during the day than at night. Conversely, it is easier to see landing light configurations and patterns at nighttime than daytime. Consequently, utilizing the same feature detector for daytime and nighttime operations may not be feasible. This paper focuses on a vision-based precision approach and landing (PAL) by comparing ORB SLAM 2, a Vision Simultaneous Localization and Mapping (VSLAM) algorithm, and a novel EKF that combines onboard IMU measurements with coplanar pose from orthography and scaling with iterations (COPOSIT). Conducting unmanned aerial system (UAS) flight tests at NASA Armstrong Flight Research Center (AFRC) with landmarks and fiducials distributed around the landing zone provides a simulated AAM approach and landing data to test vision-based PAL methods to provide Alternative Position, Navigation, and Timing (APNT) solutions for AAM PAL applications. The novel vision-based PAL EKF with IMU and COPOSIT provides accurate state estimation when distributed landmarks and fiducials are in the field of view.

distributed sensing↗
NASA NTRS1993

Validation of ISCCP cloud detections

This paper describes the validation of the International Satellite Cloud Climatology project (ISCCP)cloud detections by verifying the accuracy of the infrared clear-sky radiances. Comparison of retrieved surface temperatures to other measurements shows that bias errors are less than 2 K and random errors are about 2 K for sea surface (monthly means at 280-km scales) and that bias errors are less than 2 K and random errors are about 4 K for land surfaces (3 hourly at 280-km scales). Bias errors over a few persistently cloudy locations are sometimes -(2-4) K and over winter sea ice may be about +2 K. Surface reflectances are confirmed to be within 3% of other measurements and models for ocean, except for sun glint geometries, and to be within 3%-5% for land surfaces. Sufficiently accurate validation data are not avilable for visible reflectances of sea ice and snow-covered land, but some tests of specific cases suggest that errors are approximately 10%. These errors in clear-sky radiances suggest uncertainties in the ISCCP cloud detections of about 10% with a small (3%-6%) negative bias over land. Some specific regions exhibit both larger rms uncertainties and somewhat larger biases in cloud amount approaching 10%. ISCCP cloud detections are more in error over the polar regions than anywhere else. Based on comparisons with an anlysis of radiances measured at other wavelengths, the ISCCP analysis appears to miss 15%-25% of the clouds in summer but only 5%-10% of the winter clouds.

Rossow, William B.↗
NASA NTRS2000

Robust detection of ionospheric irregularities

The approach outlined in this paper conservatively bounds the ionospheric errors even for the worst observed ionospheric conditions to date, using data sets taken from the operational receivers in the WAAS reference station network.

Wide Area Augmentation System (WAAS) ionosphere ir↗