Search NASA⌕ Search

SEARCH · Search NASA

Results for “behavioral pattern”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Atomic-Scale Visualization of Quasiparticle Interference on a Type-II Weyl Semimetal Surface

Here we combine quasiparticle interference simulation (theory) and atomic resolution scanning tunneling spectromicroscopy (experiment) to visualize the interference patterns on a type-II Weyl semimetal Mo x W 1-x Te 2 for the first time. Our simulation based on first-principles band topology theoretically reveals the surface electron scattering behavior. We identify the topological Fermi arc states and reveal the scattering properties of the surface states in Mo 0.66 W 0.34 Te 2 . In addition, our result reveals an experimental signature of the topology via the interconnectivity of bulk and surface states, which is essential for understanding the unusual nature of this material.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

In Situ Synchrotron X-ray Study of the Mechanical Properties of Pure Mg Produced by Powder Metallurgy

In this study, in situ synchrotron X-ray experiments with wide-angle X-ray scattering (WAXS) and small-angle X-ray scattering (SAXS) detectors were performed on two pure magnesium materials produced by powder metallurgy. According to SAXS analysis, each of the two materials has a porosity of less than 0.5%. Line broadening analysis was performed on diffraction patterns collected by WAXS to analyze the dislocation evolution during material deformation. In both materials, $<$a$>$-type dislocation activities dominate the tensile deformation. The influence of grain size and texture on the different tensile behaviors of these two materials is also discussed.

line profile analysis (LPA)↗
NASA NTRS1977

New features of global climatology revealed by satellite-derived oceanic rainfall maps

Quantitative rainfall maps over the oceanic areas of the globe were derived from the Nimbus 5 Electrically Scanning Microwave Radiometer (ESMR) data. Analysis of satellite derived oceanic rainfall maps reveal certain distinctive characteristics of global patterns for the years 1973-74. The main ones are (1) the forking of the Intertropical Convergence Zone in the Pacific, (2) a previously unrecognized rain area in the South Atlantic, (3) the bimodal behavior of rainbelts in the Indian Ocean and (4) the large interannual variability in oceanic rainfall. These features are discussed.

Rao, M. S. V.↗
NASA NTRS1990

Thermal buoyancy and Marangoni convection in a two fluid layered system - A numerical study

Thermal buoyancy and surface tension driven convection is numerically investigated in a system with two, immiscible fluids. The geometry investigated, has an open cavity configuration with the lighter fluid situated on top of the heavier fluid, forming a stable layered system. The upper fluid meniscus and the interface are assumed to be flat and undeformable in the calculations. The governing equations and boundary/interface conditions are solved by a control volume based finite difference scheme for two pairs of immiscible fluids; the water-hexadecane system and a so called generic system. The steady state calculations show, that dramatically different flows are predicted when the interfacial tension effects are included or excluded from the system model. These differences are particularly appreciable in surface tension dominated flows, that are typical of microgravity situations. Complex flow patterns, with induced secondary flows are noticed in both the fluids. In general, the overall system heat transfer is found to increase with increases in the thermal buoyancy and surface tension effects, but the behavior of the system flow and thermal fields is not easy to characterize, when different combinations of these forces are considered.

Ramachandran, N.↗
NASA NTRS1990

Near-limit flame structures at low Lewis number

The characteristics of premixed gas flames in mixtures with low Lewis numbers near flammability limits were studied experimentally using a low-gravity environment to reduce buoyant convection. The behavior of such flames was found to be dominated by diffusive-thermal instabilities. For sufficiently reactive mixtures, cellular structures resulting from these instabilities were observed and found to spawn new cells in regular patterns. For less reactive mixtures, cells formed shortly after ignition but did not spawn new cells; instead these cells evolved into a flame structure composed of stationary, apparently stable spherical flamelets. Experimental observations are found to be in qualitative agreement with elementary analytical models based on the interaction of heat release due to chemical reaction, differential diffusion of thermal energy and mass, flame front curvature, and volumetric heat losses due to gas and/or soot radiation.

Ronney, Paul D.↗
NASA NTRS2012

Understanding Group/Party Affiliation Using Social Networks and Agent-Based Modeling

The dynamics of group affiliation and group dispersion is a concept that is most often studied in order for political candidates to better understand the most efficient way to conduct their campaigns. While political campaigning in the United States is a very hot topic that most politicians analyze and study, the concept of group/party affiliation presents its own area of study that producers very interesting results. One tool for examining party affiliation on a large scale is agent-based modeling (ABM), a paradigm in the modeling and simulation (M&S) field perfectly suited for aggregating individual behaviors to observe large swaths of a population. For this study agent based modeling was used in order to look at a community of agents and determine what factors can affect the group/party affiliation patterns that are present. In the agent-based model that was used for this experiment many factors were present but two main factors were used to determine the results. The results of this study show that it is possible to use agent-based modeling to explore group/party affiliation and construct a model that can mimic real world events. More importantly, the model in the study allows for the results found in a smaller community to be translated into larger experiments to determine if the results will remain present on a much larger scale.

Campbell, Kenyth↗
NASA NTRS2018

In-Flight Characterization of the Lunar Orbiter Laser Altimeter Instrument Pointing and Far-Field Pattern

The Lunar Orbiter Laser Altimeter (LOLA) aboard the Lunar Reconnaissance Orbiter (LRO) has collected nearly seven billion measurements of surface height on the Moon with an absolute accuracy of ∼1 m and a precision of ∼10 cm. Converting time-of-flight laser altimeter measurements to topographic elevations requires accurate knowledge of the laser pointing with respect to the spacecraft body-fixed coordinate system. To that end, we have utilized altimetric crossovers from LOLA, as well as bidirectional observations of the LOLA laser and receiver boresight via an Earth-based laser tracking ground station. Based on a sample of ∼780,000 globally distributed crossovers from the circular-orbit phase of LRO's mission (∼27 months), we derive corrections to the LOLA laser boresight. These corrections improve the cross-track and along-track agreement of the crossovers by 24% and 33%, respectively, yielding RMS residuals of ∼10 m. Since early in the LRO mission, the bidirectional laser tracking experiments have confirmed a pointing anomaly when the LOLA instrument is facing toward deep space or the night side of the Moon and have allowed the reconstruction of the laser far-field pattern and receiver telescope pointing. By conducting such experiments shortly after launch and nearly eight years later, we have directly measured changes in the laser characteristics and obtained critical data to understand the laser behavior and refine the instrument pointing model. The methods and results presented here are also relevant to the design, fabrication, and operation of future planetary laser altimeters and their long-term behavior in the space environment.

Barker, M. K.↗
DOE OSTI2018

Electrochemical aspects of copper atmospheric corrosion in the presence of sodium chloride

Here, this study describes the evolving state of electrolyte and corrosion processes associated with sodium chloride on copper at the initial stage of corrosion and the critical implications of this behavior on controlling kinetics and damage distributions. Sodium chloride droplets were placed on copper in humid conditions and the resulting electrolyte properties, corrosion products and damage were characterized over time using time-lapse imaging, micro Raman spectroscopy, TOF-SIMS and optical profilometry. Within minutes of NaCl droplet placement, NaOH-rich films resultant from oxygen reduction advanced stepwise from the droplets, leaving behind concentric trenching attack patterns suggestive of moving anode-cathode pairs at the alkaline film front. Corrosion attack under these spreading alkaline films was up to 10x greater than under the original NaCl drops. Furthermore, solid Cu 2 Cl(OH) 3 shells formed over the surface of the NaCl drops within hours of exposure. Thermodynamic modeling along with immersed electrochemical experiments in simulated droplet and films electrolytes were used to rationalize this behavior and build a description of the rapidly evolving corroding system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Investigating Lightning Behavior in Rapidly Intensifying Atlantic Tropical Cyclones

Lightning is a useful tool in forecasting and understanding the behavior of tropical cyclones (TCs). The Geostationary Lightning Mapper (GLM) aboard the GOES-16 geostationary satellite measures a multitude of lightning parameters, such as flash extent density (FED), average flash area (AFA) and optical energy for most of North America, South America, and the Pacific Ocean. GLM has brought about an era of spaceborne measurements to track storms many miles off the coasts and has allowed for the study of lightning throughout a TCs entire lifespan. FED has been found to be indicative of strength and intensification in TCs, but optical energy is a relatively new parameter that has not been studied intensively. This presentation analyzes the relationship between rapid intensification (RI) and GLM optical energy, AFA, and FED in Hurricanes Florence (2018) and Laura (2020). Using a 24-hour time interval in which each storm underwent RI, optical energy was analyzed from the innermost 100 kilometers of the eye and then was averaged for each minute to determine if there was a relationship between optical energy, AFA, FED, and intensification. Optical energy, FED, and AFA spiked just before RI began and then fell as the storms intensified more rapidly. These parameters increased again as intensification slowed slightly, while the optical energy peaks much lower in Hurricane Laura and much higher in Hurricane Florence. While these results show a pattern in lightning in these two TCs, further investigation of parameters like updraft strength and charge separation from microwave imagery during these secondary peaks in which optical energy behaves differently than the first peak may provide further insight as to the behavior of these TCs during RI.

Kiahna Mollette↗
NASA NTRSDate not supplied

Changes in Lightning Flash Size and Energy during the Intensification of Hurricanes Florence (2018) and Laura (2020)

Lightning is a useful tool in forecasting and understanding the behavior of tropical cyclones (TCs). The Geostationary Lightning Mapper (GLM) aboard the GOES-16 geostationary satellite measures a multitude of lightning parameters, such as flash extent density (FED), average flash area (AFA) and optical energy for most of North America, South America, and the Pacific Ocean. GLM has brought about an era of spaceborne measurements to track storms many miles off the coasts and has allowed for the study of lightning throughout a TCs entire lifespan. FED has been found to be indicative of strength and intensification in TCs, but optical energy is a relatively new parameter that has not been studied intensively. This presentation analyzes the relationship between rapid intensification (RI) and GLM optical energy, AFA, and FED in Hurricanes Florence (2018) and Laura (2020). Using a 24-hour time interval in which each storm underwent RI, optical energy was analyzed from the innermost 100 kilometers of the eye and then was averaged for each minute to determine if there was a relationship between optical energy, AFA, FED, and intensification. Optical energy, FED, and AFA spiked just before RI began and then fell as the storms intensified more rapidly. These parameters increased again as intensification slowed slightly, while the optical energy peaks much lower in Hurricane Laura and much higher in Hurricane Florence. While these results show a pattern in lightning in these two TCs, further investigation of parameters like updraft strength and charge separation from microwave imagery during these secondary peaks in which optical energy behaves differently than the first peak may provide further insight as to the behavior of these TCs during RI.

Kiahna Mollette↗
NASA NTRS1988

Human adaptation to isolated and confined environments: Preliminary findings of a seven month Antarctic winter-over human factors study

This field study was conducted during the last decade of an austral winter-over at Palmer Station in the Antarctic. The purpose of the study was to understand temporal patterns in physiological arousal and psychological mood over the course of the mission. The investigators were principally interested in how people adapted over time to chronic and acute stressors, and how people use and modify their built environment. Physiological and psychological data were collected several times a week, and information on behavior and the use of physical facilities was collected monthly. Physiological and psychological data were compared with social changes in the setting toward the development of a sequential model of human-environment transactional relationships. Based on the study results, guidelines for design of future isolated and confined environments (ICEs) included: plan space for items which make people feel at home, provide materials to allow people to personalize their environment, allow for flexible environments, provide areas for visual and auditory privacy, equip areas for socializing and remove them from private areas, and provide facilities for exercise and for projects involving physical activity. The study offers guidelines about patterns of adaption that could be expected in an ICE, discusses how these settings can be programmed to facilitate successful adjustment, and provides information about how to design future ICE habitats to maximize a healthy living environment.

Evans, Gary W.↗
DOE OSTI2015

Interface and thickness dependent domain switching and stability in Mg doped lithium niobate

Controlling ferroelectric switching in Mg doped lithium niobate (Mg:LN) is of fundamental importance for optical device and domain wall electronics applications that require precise domain patterns. Stable ferroelectric switching has been previously observed in undoped LN layers above proton exchanged (PE) phases that exhibit reduced polarization, whereas PE layers have been found to inhibit lateral domain growth. Here, Mg doping, which is known to significantly alter ferroelectric switching properties including coercive field and switching currents, is shown to inhibit domain nucleation and stability in Mg:LN above buried PE phases that allow for precise ferroelectric patterning via domain growth control. Furthermore, piezoresponse force microscopy (PFM) and switching spectroscopy PFM reveal that the voltage at which polarization switches from the “up” to the “down” state increases with increasing thickness in pure Mg:LN, whereas the voltage required for stable back switching to the original “up” state does not exhibit this thickness dependence. This behavior is consistent with the presence of an internal frozen defect field. The inhibition of domain nucleation above PE interfaces, observed in this study, is a phenomenon that occurs in Mg:LN but not in undoped samples and is mainly ascribed to a remaining frozen polarization in the PE phase that opposes polarization reversal. This reduced frozen depolarization field in the PE phase also influences the depolarization field of the Mg:LN layer above due to the presence of uncompensated polarization charge at the PE-Mg:LN boundary. These alterations in internal electric fields within the sample cause long-range lattice distortions in Mg:LN via electromechanical coupling, which were corroborated with complimentary Raman measurements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1990

Experimental and analytical study of close-coupled ventral nozzles for ASTOVL aircraft

Flow in a generic ventral nozzle system was studied experimentally and analytically with a block version of the PARC3D computational fluid dynamics program (a full Navier-Stokes equation solver) in order to evaluate the program's ability to predict system performance and internal flow patterns. For the experimental work a one-third-size model tailpipe with a single large rectangular ventral nozzle mounted normal to the tailpipe axis was tested with unheated air at steady-state pressure ratios up to 4.0. The end of the tailpipe was closed to simulate a blocked exhaust nozzle. Measurements showed about 5 1/2 percent flow-turning loss, reasonable nozzle performance coefficients, and a significant aftward axial component of thrust due to flow turning loss, reasonable nozzle performance coefficients, and a significant aftward axial component of thrust due to flow turning more than 90 deg. Flow behavior into and through the ventral duct is discussed and illustrated with paint streak flow visualization photographs. For the analytical work the same ventral system configuration was modeled with two computational grids to evaluate the effect of grid density. Both grids gave good results. The finer-grid solution produced more detailed flow patterns and predicted performance parameters, such as thrust and discharge coefficient, within 1 percent of the measured values. PARC3D flow visualization images are shown for comparison with the paint streak photographs. Modeling and computational issues encountered in the analytical work are discussed.

Mcardle, Jack G.↗
DOE OSTI2014

Intelligent feature selection techniques for pattern classification of Lamb wave signals

Lamb wave interaction with flaws is a complex, three-dimensional phenomenon, which often frustrates signal interpretation schemes based on mode arrival time shifts predicted by dispersion curves. As the flaw severity increases, scattering and mode conversion effects will often dominate the time-domain signals, obscuring available information about flaws because multiple modes may arrive on top of each other. Even for idealized flaw geometries the scattering and mode conversion behavior of Lamb waves is very complex. Here, multi-mode Lamb waves in a metal plate are propagated across a rectangular flat-bottom hole in a sequence of pitch-catch measurements corresponding to the double crosshole tomography geometry. The flaw is sequentially deepened, with the Lamb wave measurements repeated at each flaw depth. Lamb wave tomography reconstructions are used to identify which waveforms have interacted with the flaw and thereby carry information about its depth. Multiple features are extracted from each of the Lamb wave signals using wavelets, which are then fed to statistical pattern classification algorithms that identify flaw severity. In order to achieve the highest classification accuracy, an optimal feature space is required but it’s never known a priori which features are going to be best. For structural health monitoring we make use of the fact that physical flaws, such as corrosion, will only increase over time. This allows us to identify feature vectors which are topologically well-behaved by requiring that sequential classes “line up” in feature vector space. An intelligent feature selection routine is illustrated that identifies favorable class distributions in multi-dimensional feature spaces using computational homology theory. Betti numbers and formal classification accuracies are calculated for each feature space subset to establish a correlation between the topology of the class distribution and the corresponding classification accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

A mathematical discussion concerning the performance of multilayer perceptron-type artificial neural networks through use of orthogonal bipolar vectors

This work proposes the use of orthogonal bipolar vectors (OBV) as targets for multilayer perceptron (MLP) Artificial neural networks pertaining to the pattern recognition field. Implications involving this proposal are supported by a proper mathematical discussion. This study shows that the use of OBV as targets improves the class identification performance of MLP networks for pattern recognition with more than two classes when compared to the widely used conventional target bipolar vector (CBV). In addition to the overall performance improvement, it is possible to obtain high recognition rates with fewer training epochs, while keeping a feasible generalization with other data. This behavior is related to the Euclidean distance of the points in the output space, which is much higher in the case of OBVs. Therefore, with a greater distance between the points in the output space, the MLP network becomes less prone to associate trained outputs with incorrect targets. The mathematical discussion in this study is based on the backpropagation training algorithm. In addition to the mathematical discussion, results from experiments with real data are presented. These results follow those obtained by mathematical derivations. Real data sets used in the experiments are available from: (a) the Semeion Handwritten Digit of Machine Learning Repository, international repository; (b) Iris Image Database from the Chinese Academy of Sciences—CASIA; (c) Australian Sign Language, signs of Machine Learning Repository, international repository. Experiments were conducted to measure the mean Euclidean distance between the MLP network output subjected to a given input pattern and outputs related to other pattern classifications. Experimental results show that MLP networks trained with OBVs were able to ensure a Euclidean distance between the output and incorrect targets greater than MLP networks trained with CBVs (by up to 4 times for handwritten, by up to 12 times for iris images and by up to 10 times for Auslan signs language). As such, the adoption of OBVs as target vectors for MLPs reduces the computational effort for training the network.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Anisotropic 2D van der Waals Magnets Hosting 1D Spin Chains

Abstract The exploration of 1D magnetism, frequently portrayed as spin chains, constitutes an actively pursued research field that illuminates fundamental principles in many‐body problems and applications in magnonics and spintronics. The inherent reduction in dimensionality often leads to robust spin fluctuations, impacting magnetic ordering and resulting in novel magnetic phenomena. Here, structural, magnetic, and optical properties of highly anisotropic 2D van der Waals antiferromagnets that uniquely host spin chains are explored. First‐principle calculations reveal that the weakest interaction is interchain, leading to essentially 1D magnetic behavior in each layer. With the additional degree of freedom arising from its anisotropic structure, the structure is engineered by alloying, varying the 1D spin chain lengths using electron beam irradiation, or twisting for localized patterning, and spin textures are calculated, predicting robust stability of the antiferromagnetic ordering. Comparing with other spin chain magnets, these materials are anticipated to bring fresh perspectives on harvesting low‐dimensional magnetism.

1D magnetism↗
DOE OSTI2019

SoyCSN: Soybean context-specific network analysis and prediction based on tissue-specific transcriptome data

The Soybean Gene Atlas project provides a comprehensive map for understanding gene expression patterns in major soybean tissues from flower, root, leaf, nodule, seed, and shoot and stem. The RNA-Seq data generated in the project serve as a valuable resource for discovering tissue-specific transcriptome behavior of soybean genes in different tissues. We developed a computational pipeline for Soybean context-specific network (SoyCSN) inference with a suite of prediction tools to analyze, annotate, retrieve, and visualize soybean context-specific networks at both transcriptome and interactome levels. BicMix and Cross-Conditions Cluster Detection algorithms were applied to detect modules based on co-expression relationships across all the tissues. Soybean context-specific interactomes were predicted by combining soybean tissue gene expression and protein–protein interaction data. Functional analyses of these predicted networks provide insights into soybean tissue specificities. For example, under symbiotic, nitrogen-fixing conditions, the constructed soybean leaf network highlights the connection between the photosynthesis function and rhizobium–legume symbiosis. SoyCSN data and all its results are publicly available via an interactive web service within the Soybean Knowledge Base (SoyKB) at http://soykb.org/SoyCSN. SoyCSN provides a useful web-based access for exploring context specificities systematically in gene regulatory mechanisms and gene relationships for soybean researchers and molecular breeders.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Oxidation kinetic modelling of Fe-based oxygen carriers for chemical looping applications: Impact of the topochemical effect

Chemical looping is a promising technology for fossil fuel utilization due to its high fuel conversion efficiency with in-situ CO 2 capture capability. Metal oxide are used as oxygen carriers (OCs) and circulate between a fuel reactor and an air reactor to perform reduction and oxidation reactions, respectively. In general, OC exiting the fuel reactor is not reduced fully to its metallic state due to many factors including carbon deposition and OC deactivation. Therefore, the effect of the initial reduction state on the OC oxidation in the air reactor is a significant parameter for consideration in developing the oxidation kinetic model. The objective of this work is to develop a physically significant kinetic model that applies to the oxidation of both initially fully and partially reduced OC with air. For this study, 1.5 mm Fe-based OC particle supported with TiO 2 was used as the model OC particle due to its complex multistep reaction nature. The oxidation kinetics were experimentally investigated in a thermogravimetric analyzer (TGA). Results indicate a significant difference in the oxidation rate profile for the OCs when oxidized from an initially fully reduced compared to an initially partially reduced state. Elemental mapping via energy-dispersive X-ray spectroscopy (EDS) reveals a shrinking-core type topochemical pattern across the OC particle, which was identified to be the cause of the dependency of kinetics on the initial reduction state. A generalized kinetic model was developed based on the observed shrinking-core behavior without presuming any rate-determining steps and experimentally validated over a broad range of temperatures (800–1000 °C) and oxygen concentrations (5, 7, 10, and 15 mol%). Impacts of particle porosity, size, and core-shell structure on the OC oxidation kinetics were analyzed in the developed oxidation kinetic model to suggest methods of improving the oxidation rate of the OC without modifying the chemical composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗