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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 73 records · Page 4

The probability of detecting absorption features in gamma-ray burst spectra

It has recently been suggested that several mechanisms for the primary release of energy in gamma-ray bursts may result in the excitation of magnetospheric plasma oscillations (MPO) above the polar cap of a neutron star. The basic MPO idea is refined by determining the soft photon source (which damps the particle motion via inverse Compton scattering interactions) self-consistently by means of a Monte Carlo simulation for the deposition of back-scattered gamma-ray energy below the stellar photosphere. The observed fraction of bursts displaying low-energy absorption features may be understood in the context of a model wherein the overall spectrum changes with inclination angle due to the superposition of several components with different angular distributions. GRB spectra should display these cyclotron lines about 18 percent of the time, which is consistent with the KONUS and Ginga sets of data.

Melia, F.↗

Detecting point sources in EUVE survey skymaps

One of the primary goals of the Extreme Ultraviolet Explorer (EUVE) all-sky survey is the detection and identification of new sources of extreme ultraviolet radiation. Here, the challenges involved in producing a catalog containing as many statistically significant detections as possible, with a small expected number of spurious detections, are reviewed. The discussion covers simulation and testing, early survey results, advanced detection techniques, and diffuse feature detection.

Lewis, J. W.↗

A multilevel approach to sequential detection of pictorial features

The problem of detecting the local similarity between templates in a given class and a given image using a hierarchically ordered sequential decision rule is examined. It is proposed that the set of templates be partitioned and a 'representative template' be defined for each of the partitions. Several levels of partitioning are defined. Elimination of mismatching locations and termination of computation can take place at each level of detection. Each level of testing is over a more restrictive subset of the template class than the previous level. Criteria are given for selecting representative templates, the ordering of components of a template vector for error evaluation, and the threshold sequences to be used in deciding about a 'match'. Suboptimal solutions are given satisfying these criteria. Examples showing recognition of linear features in test patterns and photographs obtained by aerial and spaceborne sensors are provided.

Ramapriyan, H. K.↗

Automatic information extraction for land use and agricultural applications

Description of some current work in interpretation technique development for automatic computer-aided image information extraction related to various application areas, including land use mapping and agricultural survey and monitoring. In particular, the application of a fast template matching algorithm, employing the sequential similarity detection principle, to image registration, linear feature detection, and the extraction and enumeration of scene objects is discussed and illustrated.

Bond, A. D.↗

Feature-based Anomaly Detection System

SAND2022-7963 O The Feature-Based Anomaly Detection System detects anomalies in video data based on features derived from pre-trained image models to avoid the need for training. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Hannasch, David↗

A state-based approach to trend recognition and failure prediction for the Space Station Freedom

A state-based reasoning approach to trend recognition and failure prediction for the Altitude Determination, and Control System (ADCS) of the Space Station Freedom (SSF) is described. The problem domain is characterized by features (e.g., trends and impending failures) that develop over a variety of time spans, anywhere from several minutes to several years. Our state-based reasoning approach, coupled with intelligent data screening, allows features to be tracked as they develop in a time-dependent manner. That is, each state machine has the ability to encode a time frame for the feature it detects. As features are detected, they are recorded and can be used as input to other state machines, creating a hierarchical feature recognition scheme. Furthermore, each machine can operate independently of the others, allowing simultaneous tracking of features. State-based reasoning was implemented in the trend recognition and the prognostic modules of a prototype Space Station Freedom Maintenance and Diagnostic System (SSFMDS) developed at Honeywell's Systems and Research Center.

Nelson, Kyle S.↗

Probing transport energies and defect states in organic semiconductors using energy resolved electrochemical impedance spectroscopy

Abstract Determining the relative energies of transport states in organic semiconductors is critical to understanding the properties of electronic devices and in designing device stacks. Futhermore, defect states are also highly important and can greatly impact material properties and device performance. Recently, energy‐resolved electrochemical impedance spectroscopy (ER‐EIS) is developed to probe both the ionization energy (IE) and electron affinity (EA) as well as sub‐bandgap defect states in organic semiconductors. Herein, ER‐EIS is compared to cyclic voltammetry (CV) and photoemission spectroscopies for extracting IE and EA values, and to photothermal deflection spectroscopy (PDS) for probing defect states in both polymer and molecular organic semiconductors. The results show that ER‐EIS determined IE and EA are in better agreement with photoemission spectroscopy measurements as compared to CV for both polymer and molecular materials. Furthermore, the defect states detected by ER‐EIS agree with sub‐bandgap features detected by PDS. Surprisingly, ER‐EIS measurements of regiorandom and regioregular poly(3‐hexylthiophene) (P3HT) show clear defect bands that occur at significantly different energies. In regioregular P3HT the defect band is near the edge of the occupied states while it is near the edge of the unoccupied states in regiorandom P3HT.

14 SOLAR ENERGY↗

Image processing in remote sensing data analysis - The state of the art

Image analysis techniques applicable to remote sensing data and covering image models, feature detection, segmentation and classification, texture analysis, and matching are studied. Model types for characterizing images examined include random-field, mosaic, and facet models. Edge and corner detection as well as global extraction of linear features are discussed. Pixel clustering and classification are covered in addition to the regional approach to segmentation. Autocorrelation, second-order gray level probability density, and the use of primitive element statistics are discussed in relation to texture analysis. Finally, reducing the cost of (sub)imaging matching methods (e.g., pixelwise comparison of gray levels and normalized cross-correlation between two images) as well as improving match sharpness is considered.

Rosenfeld, A.↗

Anomaly forecasting and early warning generation

The example embodiments are directed to a system and method for forecasting anomalies in feature detection. In one example, the method includes storing feature behavior information of at least one monitoring node of an asset, including a normalcy boundary identifying normal feature behavior and abnormal feature behavior for the at least one monitoring node in feature space, receiving input signals from the at least one monitoring node of the asset and transforming the input signals into feature values in the feature space, wherein the feature values are located within the normalcy boundary, forecasting that a future feature value corresponding to a future input signal from the at least one monitoring node is going to be positioned outside the normalcy boundary based on the feature values within the normalcy boundary, and outputting information concerning the forecasted future feature value being outside the normalcy boundary for display.

Abbaszadeh, Masoud↗

White-tailed deer responses to acoustic predator cues are contingent upon past land use and contemporary fire regime

Prey can assess the immediate risk of predation by detecting cues of predator presence, and it is expected that prey should invest in costly antipredator behaviors when a cue of predator presence is detected. Features of the habitat in which the cue is detected, such as vegetative concealment, serve as indirect cues of risk and can mediate how prey respond to direct cues of predator presence. Past agricultural land use and contemporary fire regimes are common disturbances that may modify prey perceptions of risk and could, therefore, alter prey responses to direct cues of predator presence. Here we examined whether the overlap of these two disturbances affected white-tailed deer (Odocoileus virginianus) responses to cues of predator presence by measuring deer vigilance and foraging bout duration in response to coyote (Canis latrans) vocalizations across 20 woodlands that varied in past land use and contemporary fire regime. Frequent fire regimes consistently increased deer visibility to predators across both land-use history contexts. Deer exhibited no behavioral response to the predator cue in habitats containing infrequent fire regimes or agricultural legacies. Deer responded to the cue in frequently burned woodlands without agricultural legacies through increased vigilance and time spent at a foraging location. These findings reveal that land-use legacies and contemporary fire regimes can mediate how prey respond to direct cues of risk. They also suggest that prey may balance the uncertainty associated with cues of predation risk with the urgency of responding to a potential attack by being vigilant and remaining in place.

60 APPLIED LIFE SCIENCES↗

F-Hash: Feature-Based Hash Design for Time-Varying Volume Visualization via Multi-Resolution Tesseract Encoding

Interactive time-varying volume visualization is challenging due to its complex spatiotemporal features and sheer size of the dataset. Recent works transform the original discrete time-varying volumetric data into continuous Implicit Neural Representations (INR) to address the issues of compression, rendering, and super-resolution in both spatial and temporal domains. However, training the INR takes a long time to converge, especially when handling large-scale time-varying volumetric datasets. In this work, we proposed F-Hash, a novel feature-based multi-resolution Tesseract encoding architecture to greatly enhance the convergence speed compared with existing input encoding methods for modeling time-varying volumetric data. The proposed design incorporates multi-level collision-free hash functions that map dynamic 4D multi-resolution embedding grids without bucket waste, achieving high encoding capacity with compact encoding parameters. Our encoding method is agnostic to time-varying feature detection methods, making it a unified encoding solution for feature tracking and evolution visualization. Experiments show the F-Hash achieves state-of-the-art convergence speed in training various time-varying volumetric datasets for diverse features. We also proposed an adaptive ray marching algorithm to optimize the sample streaming for faster rendering of the time-varying neural representation.

deep learning↗

Prioritizing Scientific Data for Transmission

A software system has been developed for prioritizing newly acquired geological data onboard a planetary rover. The system has been designed to enable efficient use of limited communication resources by transmitting the data likely to have the most scientific value. This software operates onboard a rover by analyzing collected data, identifying potential scientific targets, and then using that information to prioritize data for transmission to Earth. Currently, the system is focused on the analysis of acquired images, although the general techniques are applicable to a wide range of data modalities. Image prioritization is performed using two main steps. In the first step, the software detects features of interest from each image. In its current application, the system is focused on visual properties of rocks. Thus, rocks are located in each image and rock properties, such as shape, texture, and albedo, are extracted from the identified rocks. In the second step, the features extracted from a group of images are used to prioritize the images using three different methods: (1) identification of key target signature (finding specific rock features the scientist has identified as important), (2) novelty detection (finding rocks we haven t seen before), and (3) representative rock sampling (finding the most average sample of each rock type). These methods use techniques such as K-means unsupervised clustering and a discrimination-based kernel classifier to rank images based on their interest level.

Castano, Rebecca↗

Disappearance of 19P/Borrelly's Silicate Feature in 2001 Apparition Is Attributed to Increase in Grain Size

We report on observations and analysis of HIFOGS 10 microns spectrophotometry of short period comet 19P/Borrelly on 2003 October 13, 15 UT at the NASA IRTF. 19P/Borrelly is one of two short period comets, comet 4PIFaye being the other, to have a silicate feature detected. During Borrelly s perihelion passage in 1994 December, a silicate feature was present with a flux-to-continuum ratio of 0.25. Two apparitions later in 2003 October, the silicate feature is absent. Thermal emission modeling using amorphous olivine and amorphous carbon shows that a slight increase in grain size accounts for the disappearance of the silicate feature. Analysis of 19P/Borrelly suggests grain size, and not the absence of olivine minerals, may be responsible for the absence of silicate features in most short period comets. 19P/Borrelly is one of the more active short period comets. However, short period comets as a family are less active than long period comets. Short period comets probably originated in the Kuiper Belt and suffered collisions while in residence in the outer solar system. Upon evolution into orbits that take them through the inner solar system, the surfaces of short period comets are exposed to sunlight through their many perihelion passages. This is in contrast to long period comets which probably originated near Jupiter and were expelled to the Oort cloud where they have existed and been exposed to cosmic ray processing. By studying the grain properties in short period comets and comparing to long period comets, we compare the effects on the grain populations of different parent body evolution histories. Upcoming opportunities to study short and long period comets will be advertised.

Wooden, D. H.↗

CALIOP and AERONET Aerosol Optical Depth Comparisons: One Size Fits None

We compare the aerosol optical depths (AOD) retrieved from backscatter measurements of the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud Aerosol Lidar Infrared Pathfinder Satellite Observations (CALIPSO) satellite with coincident Aerosol Robotic Network (AERONET) measurements. Overpass coincidence criteria of +/- 2 h and within a 40 km radius are satisfied at least once at 149 globally distributed AERONET sites from 2006 to 2010. Most data pairs (>80%) use AERONET measurements acquired +/- 30 min of the overpass. We examine the differences in AOD estimates between CALIOP and AERONET for various aerosol, environmental, and geographic conditions. Results show CALIOP AOD are lower than AERONET AOD especially at low optical depths as measured by AERONET (500 nm AOD<0.1). Furthermore, the median relative AOD difference between the two measurements is 25% of the AERONET AOD for AOD>0.1. Differences in AOD between CALIOP and AERONET are possibly due to cloud contamination, scene inhomogeneity, instrument view angle differences, CALIOP retrieval errors, and detection limits. Comparison of daytime to nighttime number of 5 km 60m (60m in the vertical) features detected by CALIOP show that there are 20% more aerosol features at night. We find that CALIPSO and AERONET do not agree on the cloudiness of scenes. Of the scenes that meet the above coincidence criteria, CALIPSO finds clouds in more than 45% of the coincident atmospheric columns AERONET classifies as clear.

Omar, A. H.↗

Tropical Pacific moisture variability

The objectives are to describe synoptic scale variability of moisture over the tropical Pacific Ocean and the systems leading to this variability; implement satellite analysis procedures in support of this effort, and to incorporate additional satellite information into operational analysis forecast systems at the National Meteorological Center (NMC). Composite satellite radiance patterns describe features detectable well before the development of synoptic scale tropical plumes. These typical features were extracted from historical files of Tiros Operational Vertical Sounder (TOVS) radiance observations for a pair of tropical plumes which developed during January 1989. Signals were inserted into the NMC operational medium range forecast model and a suite of model integrations were conducted. Many of the 48 h model errors of the historical forecasts were eliminated by the inclusion of more complete satellite observations. Three studies in satellite radiance analysis progressed. An analysis which blended TOVS moisture channels, OLR observations and European Center for Medium Weather Forecasts (ECMWF) model analysis to generate fields of total precipitable water comparable to those estimated from Scanning Multichannel Microwave Radiometer (SMMR) mu-wave observations. This study demonstrated that a 10 y climatology of precipitable water over the oceans is feasible, using available infrared observations (OLR and TOVS) and model analysis (ECMWF, NMC or similar quality). The estimates are sensitive to model quality and the estimating model must be updated with operational model changes. Coe developed a set of tropical plume and ITCZ composites from TOVS observations, and from NMC and ECMWF analyses which had been passed through a radiative transfer model to simulate TOVS radiances. The composites have been completed as well as many statistical diagnostics of individual TOVS channels. Analysis of the computations is commencing. Chung has initiated a study of the differences between TOVS observed vapor structure during El Nino Southern Oscillation (ENSO) (1983) and non-ENSO (1984) years. Preliminary diagnosis demonstrates gross moisture changes between warm and cold sea surface temperature episodes.

Mcguirk, James P.↗

Balancing Trade-Offs Imposed by Growth Media and Mass Spectrometry for Bacterial Exometabolomics

The bacterial exometabolome consists of a vast array of specialized metabolites, many of which are only produced in response to specific environmental stimuli. For this reason, it is desirable to control the extracellular environment with a defined growth medium composed of pure ingredients. However, complex (undefined) media are expected to support the robust growth of a greater variety of microorganisms than defined media. Here, we investigate the trade-offs inherent to a range of complex and defined solid media for the growth of soil microorganisms, production of specialized metabolites, and detection of these compounds using direct infusion mass spectrometry. We find that complex media support growth of more soil microorganisms, as well as allowing for the detection of more previously discovered natural products as a fraction of total m/z features detected in each sample. However, the use of complex media often caused mass spectrometer injection failures and poor-quality mass spectra, which in some cases resulted in over a quarter of samples being removed from analysis. Defined media, while more limiting in growth, generated higher quality spectra and yielded more m/z features after background subtraction. These results inform future exometabolomic experiments requiring a medium that supports the robust growth of many soil microorganisms.

59 BASIC BIOLOGICAL SCIENCES↗

Inception Based Deep Convolutional Neural Network for Remaining Useful Life Estimation of Turbofan Engines

Accurate estimation of the remaining useful life (RUL) is a key component of condition based maintenance (CBM) and prognosis and health management (PHM). Data-based models for the estimation of RUL are of particular interest because expert knowledge of systems is not always available and physical modeling is often not feasible. In this paper, a deep convolutional neural network (CNN) architecture is investigated for its ability to estimate the RUL of turbofan engines. The input to the model is a window of time series data collected from the engine under test. Inputting raw sensor data allows features to be learned instead of manually determined. To incorporate the ability to detect features of differing lengths, inception modules are used in the neural network architecture. The model is trained and tested using the new Commercial Modular Aero-Propulsion System Simulation (N-CMAPSS) data set and high prognosis accuracy was achieved. The developed model was used in the 2021 PHM Society Data Challenge and received second place, further validating its ability to accurately estimate RUL.

DeVol, Nathaniel↗

Cold atomic hydrogen in the inner galaxy

The VLA is used to measure 21 cm absorption in directions with the absolute value of b less than 1 deg., the absolute value of 1 less than 25 deg. to probe the cool atomic gas in the inner galaxy. Abundant H I absorption is detected; typical lines are deep and narrow, sometimes blending in velocity with adjacent features. Unlike 21 cm emission not all allowed velocities are covered: large portions of the l-v diagram are optically thin. Although not similar to H I emission, the absorption shows a striking correspondence with CO emission in the inner galaxy: essentially every strong feature detected in one survey is seen in the other. The provisional conclusion is that in the inner galaxy most cool atomic gas is associated with molecular cloud complexes. There are few or no cold atomic clouds devoid of molecules in the inner galaxy, although these are common in the outer galaxy.

Dickey, J. M.↗