Search NASA⌕ Search

SEARCH · Search NASA

Results for “Spatial correlation”

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 1,603 records · Page 89

Modeling of Turbulence Generated Noise in Jets

A numerically calculated Green's function is used to predict jet noise spectrum and its far-field directivity. A linearized form of Lilley's equation governs the non-causal Green s function of interest, with the non-linear terms on the right hand side identified as the source. In this paper, contributions from the so-called self- and shear-noise source terms will be discussed. A Reynolds-averaged Navier-Stokes solution yields the required mean flow as well as time- and length scales of a noise-generating turbulent eddy. A non-compact source, with exponential temporal and spatial functions, is used to describe the turbulence velocity correlation tensors. It is shown that while an exact non-causal Green's function accurately predicts the observed shift in the location of the spectrum peak with angle as well as the angularity of sound at moderate Mach numbers, at high subsonic and supersonic acoustic Mach numbers the polar directivity of radiated sound is not entirely captured by this Green's function. Results presented for Mach 0.5 and 0.9 isothermal jets, as well as a Mach 0.8 hot jet conclude that near the peak radiation angle a different source/Green's function convolution integral may be required in order to capture the peak observed directivity of jet noise.

Khavaran, Abbas↗

A new light on caloric test--what was disclosed by three dimensional analysis of caloric nystagmus?

For better understanding of caloric nystagmus, this phenomenon will be reviewed historically in three stages. 1) The first light on caloric nystagmus was thrown by Barany 1906. Through direct observation of eye movements, Barany established the caloric test as an important tool to determine the side of lesion for vertigo. 2) The second light is shed by electrooculogram (EOG) from the late 1950th. EOG enabled qualitative analysis of caloric nystagmus, and proved Barany's convection theory, but resulted in neglect of vertical and roll eye movements. 3) The third light is gained by 3D recording of eye movements started from the late 1980th. 3D recordings of eye movements enabled us to analyze the spatial orientation of caloric nystagmus, and disclose the close correlation of the nystagmus components in the head vertical and the space vertical planes, suggesting a contribution of the velocity storage integrator. The 3D property of caloric nystagmus will be explained in detail.

Caloric Tests/history↗

A Geostatistical Data Fusion Technique for Merging Remote Sensing and Ground-Based Observations of Aerosol Optical Thickness

Particles in the atmosphere reflect incoming sunlight, tending to cool the Earth below. Some particles, such as soot, also absorb sunlight, which tens to warm the ambient atmosphere. Aerosol optical depth (AOD) is a measure of the amount of particulate matter in the atmosphere, and is a key input to computer models that simulate and predict Earth's changing climate. The global AOD products from the Multi-angle Imaging SpectroRadiometer (MISR) and the MODerate resolution Imaging Spectroradiometer (MODIS), both of which fly on the NASA Earth Observing System's Terra satellite, provide complementary views of the particles in the atmosphere. Whereas MODIS offers global coverage about four times as frequent as MISR, the multi-angle data makes it possible to separate the surface and atmospheric contributions to the observed top-of-atmosphere radiances, and also to more effectively discriminate particle type. Surface-based AERONET sun photometers retrieve AOD with smaller uncertainties than the satellite instruments, but only at a few fixed locations. So there are clear reasons to combine these data sets in a way that takes advantage of their respective strengths. This paper represents an effort at combining MISR, MODIS and AERONET AOD products over the continental US, using a common spatial statistical technique called kriging. The technique uses the correlation between the satellite data and the "ground-truth" sun photometer observations to assign uncertainty to the satellite data on a region-by-region basis. The larger fraction of the sun photometer variance that is duplicated by the satellite data, the higher the confidence assigned to the satellite data in that region. In the Western and Central US, MISR AOD correlation with AERONET are significantly higher than those with MODIS, likely due to bright surfaces in these regions, which pose greater challenges for the single-view MODIS retrievals. In the east, MODIS correlations are higher, due to more frequent sampling of the varying AOD. These results demonstrate how the MISR and MODIS aerosol products are complementary. The underlying technique also provides one method for combining these products in such a way that takes advantage of the strengths of each, in the places and times when they are maximal, and in addition, yields an estimate of the associated uncertainties in space and time.

Chatterjee, Abhishek↗

Consistency of Vegetation Index Seasonality Across the Amazon Rainforest

Vegetation indices (VIs) calculated from remotely sensed reflectance are widely used tools for characterizing the extent and status of vegetated areas. Recently, however, their capability to monitor the Amazon forest phenology has been intensely scrutinized. In this study, we analyze the consistency of VIs seasonal patterns obtained from two MODIS products: the Collection 5 BRDF product (MCD43) and the Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC). The spatio-temporal patterns of the VIs were also compared with field measured leaf litterfall, gross ecosystem productivity and active microwave data. Our results show that significant seasonal patterns are observed in all VIs after the removal of view-illumination effects and cloud contamination. However, we demonstrate inconsistencies in the characteristics of seasonal patterns between different VIs and MODIS products. We demonstrate that differences in the original reflectance band values form a major source of discrepancy between MODIS VI products. The MAIAC atmospheric correction algorithm significantly reduces noise signals in the red and blue bands. Another important source of discrepancy is caused by differences in the availability of clear-sky data, as the MAIAC product allows increased availability of valid pixels in the equatorial Amazon. Finally, differences in VIs seasonal patterns were also caused by MODIS collection 5 calibration degradation. The correlation of remote sensing and field data also varied spatially, leading to different temporal offsets between VIs, active microwave and field measured data. We conclude that recent improvements in the MAIAC product have led to changes in the characteristics of spatio-temporal patterns of VIs seasonality across the Amazon forest, when compared to the MCD43 product. Nevertheless, despite improved quality and reduced uncertainties in the MAIAC product, a robust biophysical interpretation of VIs seasonality is still missing.

MAIAC↗

Coordinated Analysis of Organic Matter in Primitive Meteorites

Carbonaceous chondrites (CC) preserve a diverse range of organic matter formed within cold interstellar environments, the solar nebula, and during subsequent parent body asteroidal processing. This organic matter maintains a unique geochemical and istopic record of organic evolution [1-4]. Bulk studies of organics within CC have revealed a complex array of organic species. However, bulk studies invariably involve solvent extraction, resulting in a loss of spatial context of the host mineral matrix [3, 5]. Correlated in situ chemical and isotopic studies suggest preservation of interstellar organics in the form of spherical, often hollow, micrometer sized organic nano-globules. Nanoglobules often exhibit significant delta 15N and delta D enrichments that imply formation through fractionation of ion-molecule reactions within cold molecular clouds and/or the outer protoplanetary disk [5]. In situ studies such as 6-8 are necessary to understand the organic evolutionary stages of nanoglobules and other components in the nebula and parent body [7]. We carried out coordinated in situ micrometer-scale chemical, mineralogical and isotopic studies of the Murchison (CM2), QUE 99177 (CR3), and Tagish Lake (C2 Ung) CC. These studies were performed using fluorescent microscopy, two-step laser mass spectrometry (microL2MS), NanoSIMS, and Scanning Electron Microscopy (SEM) with Energy Dispersive X-Ray Spectroscopy (EDX). Comparative analysis of three different meteorites will help reveal the effects of parent body processes on the chemistry and isotopic composition of organic matter.

meteorites↗

Probing Supraglacial Debris on Mars 2: Crater Morphology

Lobate debris aprons (LDA), lineated valley fill (LVF), and concentric crater fill (CCF) on Mars, interpreted to bedebris-covered glaciers, possess craters with a suite of distinct interior landforms (called "ring-mold craters")that have been attributed to the presence of glacial ice at depth or surface modification processes. We testedcurrent hypotheses for the formation of ring-mold craters by conducting a comprehensive analysis of the size andmorphology of 16,457 impact craters 125m in diameter formed within glacial deposits in DeuteronilusMensae. Two major groups, bowl-shaped craters and ring-mold craters, are found, with at least nine distinctcrater types. While there is statistical difference in median diameters between these crater types, this differenceis relatively small and is within the estimated uncertainty in diameter measurements and may be related to moreenhanced erosion of the rims of ring-mold craters. Clear degradation sequences are observed, supporting a rolefor post-impact modification in producing at least some of the diversity in crater landforms. The spatial densityof ring-mold craters is also directly correlated with the development of LDA, LVF, and CCF surface textures. Flowlineations cross-cut two ring-mold crater types but they maintain their circular planforms in some cases, suggestingthat the craters initially formed completely within mantling layers deposited after glacial flow hadceased. We also find analogous craters in non-glacial units; glacial ice is therefore not required to form theobserved morphologic diversity. Our observations are most consistent with formation of crater landforms byemplacement and modification of at least two depositional episodes of icy dust (i.e., "mantle"). This mantle wasinitially tens of meters in thickness to support crater formation, and has experienced much downwasting anderosion since emplacement. Derived crater retention ages of 460 Ma for LDA, LVF, and CCF features in the regiontherefore reflect deposition of mantle units and only give a very minimum age for the formation of LDA, LVF, andCCF

Geological↗

Quantifying Methane Leak Emissions by Fused Airborne Imaging Spectroscopy with in Situ Surface Mobile and Airborne Observations of a California Producing Oil Field

Methane (CH4) emission budgets remain uncertain and are projected to grow as oil and gas production from short-lived wells increases and their subsequent transport through aging gas distribution networks. Orders-of-magnitude variations in temporal, spatial, and emission scales present a key challenge to leak detection and quantification. Also, the probability distributions for large and stochastic, leaky systems such as geological reservoirs (by natural migration-seeps) and petroleum production from those reservoirs remain largely unknown, needed to address current approach limitations. The scale of many petroleum systems favors remote sensing, but the sensitivity of such systems often precludes detection of weak emissions. Consequently, an accurate evaluation requires that the relative contribution from the emission "tails" of small leaks also be quantified, which is best carried out using high-sensitivity in situ methods. Fusion of remote sensing and in situ approaches leverages complementary capabilities to address these limitations. We show results from mobile surface (AMOG) and airborne in situ (AJAX) and thermal-infrared (TIR) hyperspectral imaging spectroscopy (Mako) data applied to a producing oil field in the California Central Valley near Bakersfield. AMOG is an automobile-based mobile lab that measures 13 trace gases, aerosol size distributions and vertical profiles, 3D winds and other meteorology, and atmospheric column measurements by solar spectroscopy at highway speeds. AJAX measures 5 trace gases and 3D winds at ~140 m/s. Mako is a broad-area TIR imaging spectrometer that can discriminate multiple gases present in each pixel acquired. In situ-derived, total field emissions were 31±16 Gg/yr CH4. This was compared with Mako-derived emissions from all plumes identified across the study site. We found that super-emitters were not the dominant emissions mode and the spatial pattern of plume locations from production infrastructure was correlated to geological structures.

Leifer, Ira↗

Ice Accretion Roughness Variations on a Hybrid CRM65-Midspan Wing Model

Ice accretion roughness measurements were performed in the Icing Research Tunnel (IRT) at NASA Glenn Research Center for the Hybrid CRM65-Midspan model in a range of icing conditions. The Hybrid CRM65-Midspan model was chosen for this investigation because 1) the model exhibits high sweep relative to models previously explored in the roughness investigations, 2) the model has leading edge characteristics similar to wing shapes currently used in mid-size commercial airliners, and 3) the sweep and thickness ratios relate better to hybrid lifting body designs for N+2 and N+3 vehicles than other models available. The investigation consisted of multiple sets of tests which focused on 1) 0-angle of attack cases replicating the conditions employed by Anderson et al. (1998) using both Appendix C and SLD cloud conditions, 2) cases based on the “Max Scallop” case by Broeren et al. (2016) and a “High Temperature” case with cloud properties similar to the “Max Scallop” case. Additional tests were performed 1) based on the “Max Scallop” case with variations in freestream static temperature and 2) using test section speeds near 10,000-hold flight conditions. The point clouds were characterized using the approach of McClain and Kreeger (2013) for the ice roughness variations and using the approach of McClain (2016) for the mean ice thickness variations. The resulting roughness and mean thickness variations generally follow the temporal scaling previously identified using on airfoil models without sweep, but the collapse of the time progression profiles is not as tight as found for past measurements on models without sweep. LEWICE and modified panel-method predictions were used explore spatial roughness variations and to compare to the roughness correlations developed by McClain et al. (2021) for the “Max Scallop” cases.

Icing↗

Azimuthal Size Scales of Solar Wind Periodic Density Structures

Periodic Density Structures (PDSs) are quasi-periodic variations of solar wind density ranging from a few minutes to a few hours. PDSs advect with the solar wind and have radial length scales (Lx) of tens to several thousand Mm, thus belonging to the class of “mesoscale structures”. Current interplanetary multi-spacecraft observations are not at spatial separations capable of directly measuring the 3D size scale of PDSs or other mesoscale structures. Instead, previous investigations estimated characteristic spatial scales in solar wind parameters using cross-correlation and/or coherence analysis applied to multi-spacecraft observations. For solar wind density and interplanetary magnetic field (IMF) intensity, the reported size scales perpendicular to the Sun-Earth line (Ly) ranged between ≈30 and ≈200 Earth Radii (RE). Here, we implemented a similar approach on the same parameters but focused on high density slow solar wind intervals with PDSs observed by the Wind and ARTEMIS-P1 spacecraft. Additionally, this is the first statistical study of the IMF intensity periodicities in relation to PDSs. We identified intervals in which the two spacecraft observed the same periodicity obtaining two PDS groups based on their radial length scale: Lx1 ≈86RE and Lx2 ≈35RE. Then, we classified the events based on the periodic variations’ coherence level. Reproducing the results with simulations of the PDSs’ transit, we inferred the Ly order of magnitudes for the two PDS groups: Ly1 ≈340RE and Ly2 ≈187RE. Knowing the PDSs’ size scales is fundamental to constrain models aimed at reproducing these structures and is critical to better understand the PDS-magnetosphere coupling.

Interplanetary physics↗

Deeply virtual Compton scattering cross sections with CLAS and generalized parton distributions

Generalized parton distributions (GPDs) are the object of an intense research effort. Among other aspects, they allow us to unravel the correlation between the longitudinal momentum fraction and the transverse spatial distributions of quarks and gluons inside the nucleon. Of particular interest is that GPDs provide access to the orbital angular momentum of the partons in the nucleon. Deeply virtual Compton scattering (DVCS), the electroproduction of a real photon on a single parton of the nucleon eN --> eNy, is the most straightforward deep exclusive process allowing access to GPDs. The CEBAF Large Acceptance Spectrometer (CLAS) at JLab plays a key role in the study of the DVCS process. Using CEBAF's 5.75 GeV polarized electron beam, an unpolarized hydrogen target, and the CLAS detector, we collected DVCS events in the widest kinematic range ever explored in the valence region: 1 epy unpolarized cross section and beam-polarized cross section difference. We will show the constraints on the GPDs which can be extracted from these results, in a nearly model-independent fitting procedure.

Jo, Hyon-Suk↗

Nowcasting Earthquakes: Imaging the Earthquake Cycle in California With Machine Learning

We propose a new machine learning-based method for nowcasting earthquakes to image the time-dependent earthquake cycle. The result is a timeseries that may correspond to the process of stress accumulation and release. The timeseries are constructed by using principal component analysis of regional seismicity. The patterns are found as eigenvectors of the cross-correlation matrix of a collection of seismicity timeseries in a coarse grained regional spatial grid (pattern recognition via unsupervised machine learning). The eigenvalues of this matrix represent the relative importance of the various eigenpatterns. Using the eigenvectors and eigenvalues, we compute the weighted correlation timeseries of the regional seismicity. This timeseries has the property that the weighted correlation generally decreases prior to major earthquakes in the region, and increases suddenly just after a major earthquake occurs. As in a previous paper, we find that this method produces a nowcasting timeseries that resembles the hypothesized regional stress accumulation and release process characterizing the earthquake cycle. We then address the problem of whether the timeseries contain information regarding future large earthquakes. For this, we compute a receiver operating characteristic and determine the decision thresholds for several future time periods of interest (optimization via supervised machine learning). We find that signals can be detected that can be used to characterize the information content of the timeseries. These signals may be useful in assessing present and near-future seismic hazards.

58 GEOSCIENCES↗

The Barberplaid illusion: Even Perceived Plaid Motion is Biased by Asymmetric Apertures

Our results show that the perceived direction of motion of plaids windowed by asymmetric spatial Gaussians is biased toward the long axis of the window. The bias increases as the relative angle between the plaid motion and the window increases, peaks at a relative angle of about 40 degrees, and then decreases. The peak bias was 14 degrees for a spatial frequency of 0.6 cpd and a window aspect ratio of 4.0. The biases increase as the window is elongated and decrease as the component spatial frequency increases. We tested the predictions of several models of human motion processing (cross correlation, motion energy, intersection of constraints, and vector sum), and show that none of these can predict our data. These results suggest that spatial integration of motion signals plays a crucial role in the perception of plaid motion.

Beutter, Brent↗

Discriminability measures for predicting readability of text on textured backgrounds

Several discriminability measures were examined for their ability to predict reading search times for three levels of text contrast and a range of backgrounds (plain, a periodic texture, and four spatial-frequency-filtered textures created from the periodic texture). Search times indicate that these background variations only affect readability when the text contrast is low, and that spatial frequency content of the background affects readability. These results were not well predicted by the single variables of text contrast (Spearman rank correlation = -0.64) and background RMS contrast (0.08), but a global masking index and a spatial-frequency-selective masking index led to better predictions (-0.84 and -0.81, respectively). c2000 Optical Society of America.

NASA Discipline Space Human Factors↗

Ab-initio simulations of chemical stability indicators of the bis-DGA-type molecule and its radiation degradation products

For hydrometallurgical treatment of the high level liquid waste (HLLW) in the DIAMEX and SANEX processes, organic compounds of the bis-DGA family are used as cation extractants in apolar solvents. For the compound of m-xylylene-bis-diglycolamide high distribution coefficients for Eu and Am were found. Since the environment of the process is highly radioactive and acidic (nitric acid), it is necessary to ensure the stability of the extractants. In order to analyse the process theoretically, the molecule of m-xylylene-bis- diglycolamide and two of its degradation products were simulated by the DFT computational methods (PBE, RPBE, BLYP, B3LYP) available within the simulation environment DMol{sup 3} 6.1 and Gaussian 09 software. The local chemical stability of some locations of the molecule was assessed from the calculated stability indicators (electrostatic potential, Fukui function, HOMO localization). In connection with the chemical treatment, especially the stability against an electrophilic attack was tested. The results of calculated bond orders and spatial distribution of electrostatic potential and HOMO were are successfully correlated with the local and general stability determined by the experiment. These results should be helpful for the further development of the separation process. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Possible Correlations between the Emission Properties of SGRBs and Their Offsets from the Host Galaxies

Short gamma-ray bursts (SGRBs) are widely believed to be from mergers of binary compact objects involving at least one neutron star and hence have a broad range of spatial offsets from their host galaxies. In this work, we search for possible correlations between the emission properties of 18 SGRBs and their offsets from the host galaxies. The SGRBs with and without extended emission do not show significant differences between their offset distributions, in agreement with some previous works. There are, however, possible correlations between the optical and X-ray afterglow emission and the offsets. The underlying physical origins are examined.

79 ASTRONOMY AND ASTROPHYSICS↗

Planning for cooler communities: Vacant lots as components of heat resilience in Mesa, Arizona

Vacant lots are often perceived as contributing to negative socioeconomic and environmental impacts on surrounding communities. However, they also offer opportunities for strategic interventions that promote heat resilience. This study uses a decision-scale congruence analytic approach to examine the correlation between extreme heat and community resilience in the context of vacant lots in the city of Mesa, Arizona. By identifying and analyzing over 1,200 vacant lots, we assessed spatial patterns of Community Resilience Estimates (CRE) for Heat and Body Heat Storage (BHS) to understand their correlation at the unit of analysis of vacant lots, where key decisions are made concerning land use. The results reveal a nonrandom spatial distribution of CRE for Heat and BHS across Mesa’s vacant lots. Vacant lots are disproportionately concentrated in neighborhoods with lower resilience, exacerbating heat exposure. Communities with limited access to cooling infrastructure, tree canopy, and other resources experience lowered heat resilience. A positive correlation between CRE for Heat and BHS shows that areas with higher heat exposure tend to have lower community resilience, reinforcing the need for cooling interventions. This study highlights the potential for converting vacant lots into heat-resilient, community-serving spaces. Using our findings, decision makers can identify priority areas and leverage vacant lots to mitigate heat impacts and foster community resilience.

community resilience↗

Nearest neighbour distributions: New statistical measures for cosmological clustering

ABSTRACT The use of summary statistics beyond the two-point correlation function to analyse the non-Gaussian clustering on small scales, and thereby, increasing the sensitivity to the underlying cosmological parameters, is an active field of research in cosmology. In this paper, we explore a set of new summary statistics – the k-Nearest Neighbour Cumulative Distribution Functions (kNN-CDF). This is the empirical cumulative distribution function of distances from a set of volume-filling, Poisson distributed random points to the k-nearest data points, and is sensitive to all connected N-point correlations in the data. The kNN-CDF can be used to measure counts in cell, void probability distributions, and higher N-point correlation functions, all using the same formalism exploiting fast searches with spatial tree data structures. We demonstrate how it can be computed efficiently from various data sets – both discrete points, and the generalization for continuous fields. We use data from a large suite of N-body simulations to explore the sensitivity of this new statistic to various cosmological parameters, compared to the two-point correlation function, while using the same range of scales. We demonstrate that the use of kNN-CDF improves the constraints on the cosmological parameters by more than a factor of 2 when applied to the clustering of dark matter in the range of scales between 10 and $40\, h^{-1}\, {\rm Mpc}$. We also show that relative improvement is even greater when applied on the same scales to the clustering of haloes in the simulations at a fixed number density, both in real space, as well as in redshift space. Since the kNN-CDF are sensitive to all higher order connected correlation functions in the data, the gains over traditional two-point analyses are expected to grow as progressively smaller scales are included in the analysis of cosmological data, provided the higher order correlation functions are sensitive to cosmology on the scales of interest.

79 ASTRONOMY AND ASTROPHYSICS↗

Temporal and Spatial Variations in Fine and Coarse Particles in Seoul, Korea

Concentrations of fine (PM2.5) and coarse particles (PM10 -2.5), whose diameters are less 2.5 µm, and between 2.5 and 10 µm, respectively, at ambient air monitoring stations in Seoul between 2002 and 2008 were analyzed. Effects of Asian dust are mainly manifested as concentration spikes of PM10 - 2.5 but were considerable on PM2.5 levels in 2002 when Asian dust storms were the strongest. Excluding the effects of Asian dust, annual average PM2.5 showed a downward trend. Despite a similarity in year - to - year variations, PM10- 2.5, mostly affected by fugitive dust emissions, and CO and NO2, primarily affected by motor vehicle emissions, did not show a decrease. PM2.5 along with CO and NO2 had the highest values during the morning rush hour. PM10 - 2.5 peak lagged about one hour behind that of PM2.5 because of fugitive dust emissions despite an increasing mixing height. On high PM2.5 days, PM2. 5 peaks occurred two hours later than usual as the effects of secondary formation became more important. A test for the spatial variabilities shows that PM10 - 2.5, which is known to be greatly influenced by local effects, is lower in its correlation coeffic ient and higher in its coefficient of divergence (COD, which serves as an indicator for spatial variability) than PM2.5, albeit that the difference between the two is small. The average COD of PM2.5 among monitoring stations was about 0.2 but was lowered t o 0.13 when considering high PM2.5 days only, which signifies that spatial uniformity increases significantly.

Fugitive dust↗