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At least 505 records · Page 28

Anomaly detection of turbopump vibration in Space Shuttle Main Engine using statistics and neural networks

The statistical and neural networks methods have been applied to investigate the feasibility in detecting anomalies in turbopump vibration of SSME. The anomalies are detected based on the amplitude of peaks of fundamental and harmonic frequencies in the power spectral density. These data are reduced to the proper format from sensor data measured by strain gauges and accelerometers. Both methods are feasible to detect the vibration anomalies. The statistical method requires sufficient data points to establish a reasonable statistical distribution data bank. This method is applicable for on-line operation. The neural networks method also needs to have enough data basis to train the neural networks. The testing procedure can be utilized at any time so long as the characteristics of components remain unchanged.

Lo, C. F.↗

Propagation directions of hydromagnetic waves in interplanetary space - Pioneer 10 and 11

The real and imaginary parts of spectral matrices of magnetic field fluctuations near 4 and 5 AU are used separately to generate estimates of hydromagnetic wave normal directions over the frequency range 0.00001 to 0.01 Hz in the spacecraft frame. Both procedures suggest the predominance of the Alfven mode over the fast and slow MHD modes among transverse magnetic field perturbations. Both procedures also show that the Alfven mode is more common among transverse perturbations at 4 AU than at 5 AU. Statistical techniques are for estimating uncertainties in computed wave normal directions and it is concluded that the real parts of the spectral matrices are more useful than the imaginary parts in specifying wave normals at times of magnetic quiet in the solar wind near 4 and 5 AU.

Parker, G. D.↗

Hyperspectral Detection of the Fluorescence Shift between Chirality-Sorted Empty and Water-Filled Single-Wall Carbon Nanotube Enantiomers

Single-wall carbon nanotubes (SWCNTs) have extraordinary electronic and optical properties that depend strongly on their exact chiral structure and their interaction with their inner and outer environment. The fluorescence (PL) of semiconducting SWCNTs, for instance, will shift depending on the molecules with which the SWCNT’s hollow core is filled. These interaction-induced shifts are challenging to resolve on the ensemble level in samples containing a mixture of different filling contents due to the relatively large inhomogeneous line width of the ensemble SWCNT PL compared to the size of these shifts. To circumvent this inhomogeneous broadening, single-tube spectroscopy and hyperspectral imaging are often applied, which until now required time-consuming statistical studies. Here, we present hyperspectral PL microscopy combined with automated SWCNT segmenting based on either principal component analysis or a convolutional neural network, capable of both spatially and spectrally resolving the PL along the length of many individual SWCNTs at the same time and automatically fitting peak positions and line widths of individual SWCNTs. The methodology is demonstrated by accurately determining the emission shifts and line widths of thousands of left- and right-handed empty and water-filled SWCNTs coated with a chiral surfactant, resulting in four statistical distributions which cannot be resolved in ensemble spectroscopy of unsorted samples. The results demonstrate a robust method to quickly probe ensemble properties with single-enantiomer spectral resolution. Moreover, it promises to be an absolute quantitative method to characterize the relative abundances of SWCNTs with different handedness or filling content in macroscopic samples, simply by counting individual species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spectral estimation of green leaf area index of oats

Green leaf area index (LAI) is a measure of vegetative growth and development and is frequently used as an input parameter in yield estimation and evapotranspiration models. Extensive destructive sampling is usually required to achieve accurate estimates of green LAI in natural situations. In this investigation, a statistical modeling approach was used to predict the green LAI of oats from bidirectional reflectance data collected with multiband radiometers. Stepwise multiple regression models based on two sets of spectral reflectance factors accounted for 73 percent and 65 percent of the variance in green LAI of oats. Exponential models of spectral data transformations of greenness, normalized difference, and near-infrared/red ratio accounted for more of the variance in green LAI than the multiple regression models.

Best, R. G.↗

Application of multispectral scanner data to the study of an abandoned surface coal mine

The utility of aircraft multispectral scanner data for describing the land cover features of an abandoned contour-mined coal mine is considered. The data were obtained with an 11 band multispectral scanner at an altitude of 1.2 kilometers. Supervised, maximum-likelihood statistical classifications of the data were made to establish land-cover classes and also to describe in more detail the barren surface features as they may pertain to the reclamation or restoration of the area. The scanner data for the surface-water areas were studied to establish the variability and range of the spectral signatures. Both day and night thermal images of the area are presented. The results of the study show that a high degree of statistical separation can be obtained from the multispectral scanner data for the various land-cover features.

Spisz, E. W.↗

Resolving turbulent magnetohydrodynamics: a hybrid operator-diffusion framework

We present a hybrid machine learning framework that combines physics-informed neural operators (PINOs) with score-based generative diffusion models to simulate the full spatio-temporal evolution of two-dimensional, incompressible, resistive magnetohydrodynamic turbulence across a broad range of Reynolds numbers (Re). The framework leverages the equation-constrained generalization capabilities of PINOs to predict coherent, low-frequency dynamics, while a conditional diffusion model stochastically corrects high-frequency residuals, enabling accurate modeling of fully developed turbulence. Trained on a comprehensive ensemble of high-fidelity simulations with Re ϵ {100, 250, 500, 750, 1000, 3000, 10000}, the approach achieves state-of-the-art accuracy in regimes previously inaccessible to deterministic surrogates. At Re = 1000 and 3000, the model faithfully reconstructs the full spectral energy distributions of both velocity and magnetic fields late into the simulation, capturing non-Gaussian statistics, intermittent structures, and cross-field correlations with high fidelity. At extreme turbulence levels (Re = 10 000), it remains the first surrogate capable of recovering the high-wavenumber evolution of the magnetic field, preserving large-scale morphology and enabling statistically meaningful predictions.

Diffusion-Integrated Neural Operators↗

Identifying neutron sources using recoil and time-of-flight spectroscopy

Identification of neutron sources is central to nuclear physics and its applications, from planetary science to nuclear security, yet direct source discrimination from measured neutron spectra remains fundamentally elusive. Here, we introduce a Bayesian protocol that directly infers source ensembles from measured neutron spectra by combining full-spectrum template matching with probabilistic evidence evaluation. Applying this protocol to recoil and time-of-flight spectroscopy, we recover single- and two-source configurations with strong statistical significance (beyond 4⁢𝜎) at event counts as low as ∼10 3 . These results demonstrate that neutron spectral signatures can be leveraged for robust source identification, opening a new observational window for both fundamental research and operationally driven applications.

neutron physics↗

A data base and analysis program for shuttle main engine dynamic pressure measurements. Appendix B: Data base plots for SSME tests 901-290 through 901-414

A dynamic pressure data base and data base management system developed to characterize the Space Shuttle Main Engine (SSME) dynamic pressure environment is described. The data base represents dynamic pressure measurements obtained during single engine hot firing tesets of the SSME. Software is provided to permit statistical evaluation of selected measurements under specified operating conditions. An interpolation scheme is also included to estimate spectral trends with SSME power level. Flow dynamic environments in high performance rocket engines are discussed.

Coffin, T.↗

A data base and analysis program for shuttle main engine dynamic pressure measurements. Appendix F: Data base plots for SSME tests 750-120 through 750-200

A dynamic pressure data base and data base management system developed to characterize the Space Shuttle Main Engine (SSME) dynamic pressure environment is presented. The data base represents dynamic pressure measurements obtained during single engine hot firing tests of the SSME. Software is provided to permit statistical evaluation of selected measurements under specified operating conditions. An interpolation scheme is also included to estimate spectral trends with SSME power level.

Coffin, T.↗

Turbulence control on an airborne laser platform

An active flow control device to generate large-scale, periodic structures in a turbulent shear flow is developed. Together with adaptive optics, the device may be used on airborne laser platforms to reduce or eliminate optical distortion caused by the turbulence in the aircraft's boundary layer. A cyclic jet issuing from a spanwise slot is used to collect the turbulent boundary layer for a finite time and then release all of the flow instantaneously in one large eddy that convects downstream. Flow visualization and hot-film probe measurements are used together with pattern recognition algorithms to demonstrate the viability of the flow control method. A flat plate towed in a water channel is used as a test bed. The instantaneous velocity signal is used to compute important statistical quantities of the random velocity field, such as the mean, the root-mean-square, the spectral distribution, and the probability density function. When optimized for a given boundary layer, it is shown that the cyclic jet will produce periodic structures that are similar to the random, naturally occurring ones. These structures seem to trigger the onset of bursting events near the wall of the plate. Thus, the present device generates periodic structures in both the outer and inner regions of a turbulent boundary layer.

Gad-El-hak, Mohamed↗

Turbulence control on airborne laser platform

An avctive flow control device to generate large-scale, periodic structures in a turbulent shear flow is developed. Together with adaptive optics, the device may be used on airborne laser platforms to reduce or eliminate optical distortion caused by the turbulence in the aircraft's boundary layer. A flat plate towed in a water channel is used as a test bed. A cyclic jet issuing from a spanwise slot is used to collect the turbulent boundary layer for a finite time during its 'on' period. When the jet is turned 'off', all of the turbulent fluid is released instantaneously in one large eddy that convects downstream. Flow visualization and hot-film probe measurements are used together with pattern recognition algorithms to demonstrate the viability of the flow control method. The instantaneous velocity signal is used to compute important statistical quantities of the random velocity field, such as the mean, the root-mean-square, the spectral distribution, and the probability density function. When optimized for a given boundary layer, the cyclic jet produces periodic structures that are qualitatively similar to the random, naturally occurring ones. These structures seem to trigger the onset of bursting events near the wall. Thus, the present device generates periodic structures in both the outer and inner regions of a turbulent boundary layer.

Gad-El-hak, Mohamed↗

Numerical simulation of boundary layers. Part 3: Turbulence and relaminarization in sink flows

Direct numerical simulations of sink-flow boundary layers, with acceleration parameters K between 1.5 and 3.0 x 10 to the -6 power, are presented. The three-dimensional, time-dependent Navier-Stokes equations are solved numerically using a spectral method, with about 10 to the -6 degrees of freedom. The flow is assumed to be statistically steady, and self-similar. A multiple-scale approximation and periodic conditions are applied to the fluctuations. The turbulence is studied using instantaneous and statistical results. Good agreement with the experiments of Jones and Launder is observed. Two effects of the favorable pressure gradient are to extend the logarithmic layer, and to alter the energy balance of the turbulence near the edge of the boundary layer. At very low Reynolds number the logarithmic layer is shortened and slightly displaced, but wall-layer streaks are present even at the lowest values of the Reynolds number for which turbulence can be sustained. Large quiescent patches appear in the flow. Relaminarization occurs at K = 3.0 x 10 to the -6 power, corresponding to a Reynolds number, based on momentum thickness, of about 330.

Spalart, Philippe R.↗

Study of Lagrangian characteristic times using direct numerical simulation of turbulence

Direct numerical simulations and large eddy simulations of homogeneous isotropic turbulence are used to compute Lagrangian statistics of turbulence and, in particular, its time scales. The computed time scales are compared with the spectral times scales that are frequently used in Eddy Damped Quasi-Normal Markovian calculations of the spectrum. The time scale models are rather good at high wavenumber and the results point to directions for improvement of the time scales at low wavenumber.

Lee, C. H.↗

High dimensional reflectance analysis of soil organic matter

Recent breakthroughs in remote-sensing technology have led to the development of high spectral resolution imaging sensors for observation of earth surface features. This research was conducted to evaluate the effects of organic matter content and composition on narrowband soil reflectance across the visible and reflective infrared spectral ranges. Organic matter from four Indiana agricultural soils, ranging in organic C content from 0.99 to 1.72 percent, was extracted, fractionated, and purified. Six components of each soil were isolated and prepared for spectral analysis. Reflectance was measured in 210 narrow bands in the 400- to 2500-nm wavelength range. Statistical analysis of reflectance values indicated the potential of high dimensional reflectance data in specific visible, near-infrared, and middle-infrared bands to provide information about soil organic C content, but not organic matter composition. These bands also responded significantly to Fe- and Mn-oxide content.

Henderson, T. L.↗

BATSE observations of gamma-ray burst spectra. I - Spectral diversity

We studied the time-averaged gamma-ray burst spectra accumulated by the spectroscopy detectors of the Burst and Transient Source Experiment. The spectra are described well at low energy by a power-law continuum with an exponential cutoff and by a steeper power law at high energy. However, the spectral parameters vary from burst to burst with no universal values. The break in the spectrum ranges from below 100 keV to more than 1 MeV, but peaks below 200 keV with only a small fraction of the spectra breaking above 400 keV; it is therefore unlikely that a majority of the burst spectra are shaped directly by pair processes, unless bursts originate from a broad redshift range. The correlations among burst parameters do not fulfill the predictions of the cosmological models of burst origin. No correlations with burst morphology or the spatial distribution were found. We demonstrate the importance of using a complete spectral description even if a partial description (e.g., a model without a high-energy tail) is statistically satisfactory.

Band, D.↗

Compression of regions in the global advanced very high resolution radiometer 1-km data set

The global advanced very high resolution radiometer (AVHRR) 1-km data set is a 10-band image produced at USGS' EROS Data Center for the study of the world's land surfaces. The image contains masked regions for non-land areas which are identical in each band but vary between data sets. They comprise over 75 percent of this 9.7 gigabyte image. The mask is compressed once and stored separately from the land data which is compressed for each of the 10 bands. The mask is stored in a hierarchical format for multi-resolution decompression of geographic subwindows of the image. The land for each band is compressed by modifying a method that ignores fill values. This multi-spectral region compression efficiently compresses the region data and precludes fill values from interfering with land compression statistics. Results show that the masked regions in a one-byte test image (6.5 Gigabytes) compress to 0.2 percent of the 557,756,146 bytes they occupy in the original image, resulting in a compression ratio of 89.9 percent for the entire image.

Kess, Barbara L.↗

Momentum deposition on Wolf-Rayet winds: Nonisotropic diffusion with effective gray opacity

We derive the velocity and mass-loss rate of a steady state Wolf-Rayet (WR) wind, using a nonisotropic diffusion approximation applied to the transfer between strongly overlapping spectral lines. Following the approach of Friend & Castor (1983), the line list is assumed to approximate a statistically parameterized Poisson distribution in frequency, so that photon transport is controlled by an angle-dependent, effectively gray opacity. We show the nonisotropic diffusion approximation yields good agreement with more accurate numerical treatments of the radiative transfer, while providing analytic insight into wind driving by multiple scattering. We illustrate, in particular, that multiple radiative momentum deposition does not require that potons be repeatedly reflected across substantial distances within the spherical envelope, but indeed is greatest when photons undergo a nearly local diffusion, e.g., through scattering by many lines closely spaced in frequency. Our results reiterate the view that the so-called 'momentum problem' of Wolf-Rayet winds is better characterized as an 'opacity problem' of simply identfying enough lines. One way of increasing the number of thick lines in Wolf-Rayet winds is to transfer opacity from saturated to unsaturated lines, yielding a steeper opacity distribution than that found in OB winds. We discuss the implications of this perspective for extending our approach to W-R wind models that incorporate a more fundamental treatment of the ionization and excitation processes that determine the line opacity. In particular, we argue that developing statistical descriptions of the lines to allow an improved effective opacity for the line ensemble would offer several advantages for deriving such more fundamental W-R wind models.

Gayley, Kenneth G.↗