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At least 847 records · Page 47

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NASA NTRS2007

Mapped Landmark Algorithm for Precision Landing

A report discusses a computer vision algorithm for position estimation to enable precision landing during planetary descent. The Descent Image Motion Estimation System for the Mars Exploration Rovers has been used as a starting point for creating code for precision, terrain-relative navigation during planetary landing. The algorithm is designed to be general because it handles images taken at different scales and resolutions relative to the map, and can produce mapped landmark matches for any planetary terrain of sufficient texture. These matches provide a measurement of horizontal position relative to a known landing site specified on the surface map. Multiple mapped landmarks generated per image allow for automatic detection and elimination of bad matches. Attitude and position can be generated from each image; this image-based attitude measurement can be used by the onboard navigation filter to improve the attitude estimate, which will improve the position estimates. The algorithm uses normalized correlation of grayscale images, producing precise, sub-pixel images. The algorithm has been broken into two sub-algorithms: (1) FFT Map Matching (see figure), which matches a single large template by correlation in the frequency domain, and (2) Mapped Landmark Refinement, which matches many small templates by correlation in the spatial domain. Each relies on feature selection, the homography transform, and 3D image correlation. The algorithm is implemented in C++ and is rated at Technology Readiness Level (TRL) 4.

Johnson, Andrew↗

DOE OSTI2022

Tracer-field cross-correlations with k -nearest neighbour distributions

ABSTRACT In astronomy and cosmology significant effort is devoted to characterizing and understanding spatial cross-correlations between points – e.g galaxy positions, high energy neutrino arrival directions, X-ray and AGN sources, and continuous fields – e.g. weak lensing meiand Cosmic Microwave Background maps. Recently, we introduced the k-nearest neighbour (kNN) formalism to better characterize the clustering of discrete (point) data sets. Here, we extend it to the point – field cross-correlations analysis. It combines kNN measurements of the point data set with measurements of the field smoothed at many scales. The resulting statistics are sensitive to all orders in the joint clustering of the points and the field. We demonstrate that this approach, unlike the 2-pt cross-correlation, can measure the statistical dependence of two data sets even when there are no linear (Gaussian) correlations between them. We further demonstrate that this framework is far more effective than the two point function in detecting cross-correlations when the continuous field is contaminated by high levels of noise. For a particularly high level of noise, the cross-correlation between haloes and the underlying matter field in a cosmological simulation, between 10 h−1 Mpc and 30 h−1 Mpc, is detected at >5σ significance using the technique presented here, when the two-point cross-correlation significance is ∼1σ. Finally, we show that kNN cross-correlations of haloes and the matter field can be well modelled on quasi-linear scales using the Hybrid Effective Field Theory (HEFT) framework, with the same set of bias parameters as are used for 2-pt cross-correlations. The substantial improvement in the statistical power of detecting cross-correlations using this method makes it a promising tool for various cosmological applications.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1984

Research in extragalactic astrophysics

The spatial distribution of clusters of galaxies and the large scale structure of the universe is investigated. Correlations in the spatial cluster distribution are much stronger than those seen for galaxies, and over scales much larger than previously anticipated. The following main studies are completed and published; (1) The determination of the correlation functions of rich clusters of galaxies, and its dependence on richness and other parameters. Very large scale structure exists in the universe, and rich clusters participate in this structure more efficiently than galaxies. (2) A complete catalog of superclusters, is determined. The selection criteria is that of a volume density enhancement, and is done in 3 dimensions. (3) The giant galaxy void in Bootes is found to be surrouned by rich, large superclusters from the catalog described above. (4) A very large scale void of rich clusters of galaxies is found in the study of the spatial distribution of rich clusters.

Bahcall, N.↗

DOE OSTI2025

Applying Gaussian Process Machine Learning and Modern Probabilistic Programming to Satellite Data to Infer CO 2 Emissions

Satellite data provides essential insights into the spatiotemporal distribution of CO 2 concentrations. However, many atmospheric inverse models fail to adequately incorporate the spatial and temporal correlations inherent in satellite observations and often lack rigorous methods for estimating parameters like spatial length scales. We introduce an inference model that processes the spatiotemporal covariance in satellite data and estimates hyperparameters such as covariance length scales. Our approach uses the Gaussian process (GP) machine learning (ML) and modern probabilistic programming languages (PPLs) to perform atmospheric inversions of emissions from satellite data. We develop a GP ML inversion system based on modern PPLs and the GEOS-Chem chemical transport model, simulating atmospheric CO 2 concentrations corresponding to the Orbiting Carbon Observatory-2/3 (OCO-2/3) data for July 2020. In our supervised learning framework, we treat the GEOS-Chem simulated data set as the target, with predictors derived by scaling the target with sector-specific factors hidden from the GP machine. Our results show that the GP model, combined with GPU-enabled PPLs, effectively retrieves true emission scaling factors and infers noise levels concealed within the data. This suggests that our method could be applied over larger areas with more complex covariance structures, enabling comprehensive analysis of the spatiotemporal patterns observed in OCO-2/3 and similar satellite data sets.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Magnetic correlations and structure in bixbyite across the spin-glass transition

Magnetic frustration in atomically ordered crystals gives rise to a broad range of quantum phenomena. The mineral bixbyite, F e 2 - x M n x O 3 , has magnetic frustration induced by atomic disorder. The end-members M n 2 O 3 and β - F e 2 O 3 both have magnetically ordered ground states, but the bixbyite crystal studied here, with a composition F e 1.12 M n 0.88 O 3 , instead undergoes a spin-glass-like transition near 32 K. Here, the magnetic correlations and atomic structure of bixbyite are followed across the spin-glass transition using powder and single-crystal neutron scattering. Refinement of Bragg intensities from neutron diffraction data allows precise determination of the average Fe and Mn concentration on the different crystallographic sites of the structure. No structural transitions occur in bixbyite upon cooling. Using the three-dimensional magnetic difference pair distribution function (3D-mΔPDF), the magnetic correlations are resolved spatially and their temperature dependence determined. The results demonstrate that the spin-spin correlations are strong well above the glass transition temperature, consistent with the spin-glass nature of the magnetism in bixbyite.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS2006

Spatiotemporal Filtering Using Principal Component Analysis and Karhunen-Loeve Expansion Approaches for Regional GPS Network Analysis

Spatial filtering is an effective way to improve the precision of coordinate time series for regional GPS networks by reducing so-called common mode errors, thereby providing better resolution for detecting weak or transient deformation signals. The commonly used approach to regional filtering assumes that the common mode error is spatially uniform, which is a good approximation for networks of hundreds of kilometers extent, but breaks down as the spatial extent increases. A more rigorous approach should remove the assumption of spatially uniform distribution and let the data themselves reveal the spatial distribution of the common mode error. The principal component analysis (PCA) and the Karhunen-Loeve expansion (KLE) both decompose network time series into a set of temporally varying modes and their spatial responses. Therefore they provide a mathematical framework to perform spatiotemporal filtering.We apply the combination of PCA and KLE to daily station coordinate time series of the Southern California Integrated GPS Network (SCIGN) for the period 2000 to 2004. We demonstrate that spatially and temporally correlated common mode errors are the dominant error source in daily GPS solutions. The spatial characteristics of the common mode errors are close to uniform for all east, north, and vertical components, which implies a very long wavelength source for the common mode errors, compared to the spatial extent of the GPS network in southern California. Furthermore, the common mode errors exhibit temporally nonrandom patterns.

displacement↗

DOE OSTI2021

Emerging contact force heterogeneity in ordered soft granular media

Under external perturbations, inter-particle forces in disordered granular media are well known to form a heterogeneous distribution with filamentary patterns. Better understanding these forces and the distribution is important for predicting the collective behavior of granular media, the media second only to water as the most manipulated material in global industry. However, studies in this regard so far have been largely confined to granular media exhibiting only geometric heterogeneity, leaving the dimension of mechanical heterogeneity a rather uncharted area. In this work, through a FEM contact mechanics model, we show that a heterogeneous inter-particle force distribution can also emerge from the dimension of mechanical heterogeneity alone. Specifically, we numerically study inter-particle forces in packing of mechanically heterogeneous disks arranged over either a square or a hexagonal lattice and under quasi-static isotropic compression. Our results show that, at the system scale, a hexagonal packing exhibit a more heterogeneous inter-particle force distribution than a square packing does; At the particle scale, for both packing lattices, preliminary analysis shows the consistent coexistence of outliers (i.e., softer disks sustaining larger forces while stiffer disks sustaining smaller forces) in comparison to their homogeneous counterparts, which implies the existence of nonlocal effect. Further analysis on the portion of outliers and on spatial contact force correlations suggest that the hexagonal packing shows more pronounced nonlocal effect over the square packing under small mechanical heterogeneity. However, such trend is reversed when assemblies becomes more mechanically heterogeneous. Lastly, we confirm that, in the absence of particle reorganization events, contact friction merely plays the role of packing stabilization while its variation has little effect on inter-particle forces and their distribution.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Coherence Analysis of the Space Launch System using Unsteady Pressure Sensitive Paint

Transonic buffet during atmospheric ascent is a major source of unsteady loading on launch vehicles that, in the past, has led to structural failures. Thus, determining accurate buffet forcing functions (BFFs) to properly predict the vehicle response to buffet is of vital importance in launch vehicle design. The state of the art for obtaining the BFFs relies on wind-tunnel tests where the fluctuating pressures are measured by pressure transducers (PTs) at sparse locations on a rigid, geometrically-scaled buffet model. To compute the BFFs, the outer mold line (OML) of the vehicle is mapped onto contiguous panels centered at the location of the PTs and the measured fluctuating pressures are integrated over the panels’ areas. To mitigate conservatism due to the assumption that the measured buffet pressures act in phase across each panel, coherence factors are applied, effectively reducing the integration areas and, therefore, the buffet forces. For coherence factors to provide the proper level of BFF attenuation, accurate knowledge of the spatial and temporal correlation of the buffet pressures is paramount. Unfortunately, even with hundreds of unsteady pressure transducers instrumenting the models, compromises must be made on the spatial resolution of the PTs. Typically, the PT layout aims at resolving the pressure correlation along the longitudinal axis of the vehicle, assuming that coherent structures propagate mostly in the longitudinal direction. As a result, the distribution of azimuthal/cross-stream correlation is not well known and its impact on the estimated BFFs is often neglected. To fill this and other knowledge gaps, extremely high spatial-resolution uPSP data were collected for three different production-design configurations of the Space Launch System in the NASA Ames Research Center Unitary Plan Wind Tunnel 11-Foot Transonic Wind Tunnel. Specifically, two cargo configurations, the Block 1 and Block 1B, and one crew configuration, the Block 1B crew, were surveyed at resolutions ranging from 600,000 to over 1 million uPSP measurement locations. To shed light on the temporal and spectral behavior of are presented. Several OML regions and flow features of interest are investigated, from theexpansion/shock on the Orion Multi-Purpose Crew Vehicle, to the terminal shock environment on the core stage, and the Strouhal shedding behind the boosters forward attach. The sensitivity of these environments to the vehicle attitude is examined. Furthermore, for selected panels,coherence factors that accurately capture the azimuthal coherence distribution of the buffetpressures are derived and their impact on the estimated BFFs is discussed. Finally, distributions of the local convection velocity and cross spectrum phase are presented.

buffet↗

DOE OSTI2019

Stability of disordered topological superconducting phases in magnet-superconductor hybrid systems

Magnet-superconductor hybrid heterostructures constitute a promising candidate system for the quantum engineering of chiral topological superconductivity. In this work, we investigate the stability of their topological phases in the presence of various types of potential and magnetic disorder. In particular we consider magnetic disorder in the coupling strength and spin orientation, as well as percolation-type disorder representing missing magnetic moments. We show that potential disorder leads to the weakest suppression of topological phases, while percolation disorder leads to their strongest suppression. In addition, disorder can also lead to the emergence of topological phases in part of the phase diagram that are topologically trivial in a clean system. Furthermore, we demonstrate that in the case of correlated potential disorder, the spatial structure of the disorder potential is correlated not only with the particle number density, but also the Chern number density. Finally, we demonstrate how the disorder-induced destruction of topological superconductivity is reflected in the spatial structure and distribution of the Chern number density.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Online Event Detection in Synchrophasor Data with Graph Signal Processing

Online detection of anomalies is crucial to enhancing the reliability and resiliency of power systems. We propose a novel data-driven online event detection algorithm with synchrophasor data using graph signal processing. In addition to being extremely scalable, our proposed algorithm can accurately capture and leverage the spatio-temporal correlations of the streaming PMU data. This paper also develops a general technique to decouple spatial and temporal correlations in multiple time series. Finally, we develop a unique framework to construct a weighted adjacency matrix and graph Laplacian for product graph. Case studies with real-world, large-scale synchrophasor data demonstrate the scalability and accuracy of our proposed event detection algorithm. Compared to the state-of-the-art benchmark, the proposed method not only achieves higher detection accuracy but also yields higher computational efficiency.

Event detection↗

DOE OSTI2020

Online Event Detection in Synchrophasor Data with Graph Signal Processing

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2011

Estimated Accuracy of Three Common Trajectory Statistical Methods

Three well-known trajectory statistical methods (TSMs), namely concentration field (CF), concentration weighted trajectory (CWT), and potential source contribution function (PSCF) methods were tested using known sources and artificially generated data sets to determine the ability of TSMs to reproduce spatial distribution of the sources. In the works by other authors, the accuracy of the trajectory statistical methods was estimated for particular species and at specified receptor locations. We have obtained a more general statistical estimation of the accuracy of source reconstruction and have found optimum conditions to reconstruct source distributions of atmospheric trace substances. Only virtual pollutants of the primary type were considered. In real world experiments, TSMs are intended for application to a priori unknown sources. Therefore, the accuracy of TSMs has to be tested with all possible spatial distributions of sources. An ensemble of geographical distributions of virtual sources was generated. Spearman s rank order correlation coefficient between spatial distributions of the known virtual and the reconstructed sources was taken to be a quantitative measure of the accuracy. Statistical estimates of the mean correlation coefficient and a range of the most probable values of correlation coefficients were obtained. All the TSMs that were considered here showed similar close results. The maximum of the ratio of the mean correlation to the width of the correlation interval containing the most probable correlation values determines the optimum conditions for reconstruction. An optimal geographical domain roughly coincides with the area supplying most of the substance to the receptor. The optimal domain s size is dependent on the substance decay time. Under optimum reconstruction conditions, the mean correlation coefficients can reach 0.70 0.75. The boundaries of the interval with the most probable correlation values are 0.6 0.9 for the decay time of 240 h and 0.5 0.95 for the decay time of 12 h. The best results of source reconstruction can be expected for the trace substances with a decay time on the order of several days. Although the methods considered in this paper do not guarantee high accuracy they are computationally simple and fast. Using the TSMs in optimum conditions and taking into account the range of uncertainties, one can obtain a first hint on potential source areas.

Kabashnikov, Vitaliy P.↗

DOE OSTI2024

Temporal Error Correlations in a Terrestrial Carbon Cycle Model Derived by Comparison to Carbon Dioxide Eddy Covariance Flux Tower Measurements

Abstract Atmospheric CO 2 flux inversions require as input an estimate of spatial and temporal correlations of errors in their estimate of the prior mean. Some previous studies have used the differences in CO 2 daily average flux estimates produced by terrestrial carbon cycle models and eddy covariance measurements to constrain the flux error correlations. Since inversions are starting to resolve the daily cycle, we set out to examine the correlations at sub‐daily time scales, as well as the correlations across years. To this end, we examine the autocorrelations in the difference between net ecosystem‐atmosphere exchange measurements from 75 AmeriFlux towers and temporally downscaled high‐spatial‐resolution flux estimates from the Carnegie‐Ames‐Stanford Approach (CASA) terrestrial carbon cycle model. We find that the daily cycle is prominent in these hourly autocorrelations and that these autocorrelations persist across years. We propose a family of functions to model these temporal correlations in atmospheric inversions, and use cross validation to determine which of the correlation functions best fits autocorrelation data from towers not in the training set. Correlation functions with a component that attempts to model the daily cycle in the differences match correlations from other towers better than those without. Those models that reproduce the same correlation structures at 1‐year intervals while modulating the amplitudes of the correlations between those intervals improve the fit still further.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Majorana Edge Modes in Isolated Wires

Topological superconductors are believed to host exotic quasiparticle excitations known as Majorana zero modes (MZMs), with much of the evidence based on BCS mean-field theory. The direct application of mean-field arguments is tenuous in finite, isolated systems relevant in some experiments. Here, we develop a new correlation-based method for identifying MZMs in interacting, number-conserving systems. Using the density matrix renormalization group, we study fermion number-conserving models with long-range interactions, which under periodic boundary conditions exhibit robust topological and nontopological superconductivity, tuned by the strength of interaction [Ortiz et al., Phys. Rev. Lett. 113, 267002 (2014)]. We find evidence that, on the topological side, Majorana edge modes appear in open chains, manifesting as the vanishing of the energy splitting between odd- and even-parity ground states with increasing system size. Additionally, off-diagonal two-point correlation functions show nonlocal, parity-dependent edge effects. These correlations reveal the spatial structure of Majorana modes in the many-body wave function. We show that the correlation diagnostic applies broadly, including to short-range interacting models, where topological superconductivity is more fragile due to the absence of a bulk excitation gap.

Thomas-Markarian, Jaden↗

DOE OSTI2018

Viscosity and real-space molecular motion of water: Observation with inelastic x-ray scattering

Even though viscosity is one of the fundamental properties of liquids, its microscopic origin is not fully understood. We determined the spatial and temporal correlation of molecular motions of water near room temperature and its temperature variation on a picosecond timescale and a subnanometer spatial scale, through high-resolution inelastic x-ray scattering measurement. The results, expressed in terms of the time-dependent pair correlation function called the Van Hove function, show that the timescale of the decay of the molecular correlation is directly related to the Maxwell relaxation time near room temperature, which is proportional to viscosity. This conclusion validates our earlier finding that the topological changes in atomic or molecular connectivity are the origin of viscosity in liquids.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2015

Two-dimensional wave-number spectral analysis techniques for phase contrast imaging turbulence imaging data on large helical device

An analysis method for unfolding the spatially resolved wave-number spectrum and phase velocity from the 2D CO{sub 2} laser phase contrast imaging system on the large helical device is described. This is based on the magnetic shear technique which identifies propagation direction from 2D spatial Fourier analysis of images detected by a 6 × 8 detector array. Because the strongest modes have wave-number at the lower end of the instrumental k range, high resolution spectral techniques are necessary to clearly resolve the propagation direction and hence the spatial distribution of fluctuations along the probing laser beam. Multiple-spatial point cross-correlation averaging is applied before calculating the spatial power spectrum. Different methods are compared, and it is found that the maximum entropy method (MEM) gives best results. The possible generation of artifacts from the over-narrowing of spectra are investigated and found not to be a significant problem. The spatial resolution Δρ (normalized radius) around the peak wave-number, for conventional Fourier analysis, is ∼0.5, making physical interpretation difficult, while for MEM, Δρ ∼ 0.1.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1975

Jet noise source location by cross-correlation of far field microphone signals

A theoretical analysis is presented for the evaluation of correlation functions of many spatially separated noise sources in a jet. A one-dimensional model is considered in which the noise sources are located on the axis of the jet downstream of the nozzle. The theory for extracting the spatial distribution from far field cross-correlations by signal analysis is derived. The advantage of this method is that difficult numerical inversions are not needed.

Parthasarathy, S. P.↗

NASA NTRS1989

Does the far-infrared/radio correlation in spiral galaxies extend to the spatial domain

A comparison is made between the spatial distribution of the thermal far-infrared and non-thermal radio emission of nearby spiral galaxies. This is done in an attempt to improve our understanding of the well known correlation between the integrated Infrared Astronomy Satellite (IRAS) far-infrared and radio emission of spiral galaxies, e.g., de Jong et al., 1985, Helou et al., 1986. A physical explanation for this correlation is not straight forward due to the ambiguous nature of the origin of the far-infrared and radio, and the dependence of the non-thermal radio on each galaxies' magnetic field. It is now widely believed that the infrared emission detected in the longer wavelength IRAS wavebands (less than 50 microns) arises from at least two distinct sources, e.g., Cox et al., 1986, Persson and Helou, 1987: (1) a warm (T approx. 40 K) component associated with dense dust clouds heated by embedded O and B type stars; and (2) a cooler (T approx. 20 K) component associated with diffuse dust distributed throughout the interstellar matter (ISM) heated by the interstellar radiation field. A link between the warm component and the radio via electrons originating in Type II supernovae (the ultimate fate of many of the O and B type stars responsible for the warm component) has been suggested by numerous authors. The supporting evidence is scarce and inconclusive. Researchers have attempted to provide some insight into the problem by looking at the spatial distribution of the different components in some nearby spiral galaxies, starting with the face-on spiral M51. The source of the far-infrared data is the IRAS chopped photometric channel (CPC) instrument. Warm and cold far-infrared fluxes integrated over all wavelengths and the radio intensity at two frequencies are plotted against radius. All plots are to a common resolution of 100 arcsec, the radio data originating from the Cambridge Low Frequency Synthesis Telescope (151 MHz) and the VLA (1490 MHz, from Condon, 1987). The warm and cold regions are assumed to be representedby a single galactic wide temperatures of 50 K and 20 K respectively. A dust emissivity of 1 has been assumed. The form of the plots is little effected by varying these assumptions. The radio and cold component curves appear to follow each other most closely, in contradiction to the simple OB star/type II supernovae hypothesis.

Howarth, Neil A.↗