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At least 451 records · Page 25

Detection of bearing failure in mechanical devices using neural networks

We present a novel time-domain method for the detection of faulty bearings that has direct applicability to monitoring the health of the turbo pumps on the Space Shuttle Main Engine. A feed-forward neural network was trained to detect modelled roller bearing faults on the basis of the periodicity of impact pulse trains. The network's performance was dependent upon the number of pulses in the network's input window and the signal-to-noise ratio of the input signal. To test the model's validity, we fit the model's parameters to an actual vibration signal generated by a faulty roller element bearing and applied the network trained on this model to detect faults in actual vibration data. When this network was tested on the actual vibration data, it correctly identified the vibration signal as a fault condition 76 percent of the time.

Burne, Richard A.↗

Passive Microwave Remote Sensing of Rainfall Considering the Effects of Wind and Nonprecipitating Clouds

It has long been shown both in theory and in observation that emission from rain drops in a raining cloud results in upwelling brightness temperature above that caused by the sea surface alone. High brightness temperatures at microwave frequencies (e.g. 37 and 19 GHz) have usually been quantitatively associated with rainfall using physical or statistical models. By comparing concurrent special sensor microwave/imager and radar data, however, we noticed many cases where there is no appreciable rainfall in a field of view (FOV) which exhibits high brightness temperature (T(sub B)) at 37 and 19 GHz. On the basis of calculations and past literature it is shown that such high brightness temperatures can be caused by nonprecipitating clouds and by wind. The effect of the wind is to create wave and high-emissivity foam on the sea surface. A model is developed to relate T(sub B) to the fractional coverage of rain, f, within a FOV. The parameters of the model are calibrated by fitting the model to the observed brightness temperature and fractional rain coverage data. The critical parameter of the model, T(sub B min.), which is the threshold brightness temperature for the presence of rain, depends on the strength of the storm. The strength of the storm is characterized by the fraction of the FOVs within a large area that have T(sub B) higher than 240 K, which is readily obtainable from satellite data alone. The instantaneous FOV rain rate R can then be obtained through the f approximately R relationship which is empirically derived using radar data. An algorithm has been proposed based on the T(sub B) approximately f and f approximately R relationship. Application of the algorithm to TOGA-COARE and Darwin storms results in reasonable instantaneous FOV rain estimate. When averaged over the entire radar scan, a more accurate and unbiased areal rain estimate can be achieved.

Qihang Li.↗

Gamma-Ray Observations of the Supernova Remnant RX J0852.0-4622 with the Fermi Large Area Telescope

We report on gamma-ray observations of the supernova remnant (SNR) RX J0852.04622 with the Large Area Telescope (LAT) on board the Fermi Gamma-ray Space Telescope. In the Fermi-LAT data, we find a spatially extended source at the location of the SNR. The extension is consistent with the SNR size seen in other wavelengths such as X-rays and TeV gamma rays, leading to the identification of the gamma-ray source with the SNR. The spectrum is well described as a power law with a photon index of = 1.85 0.06 (stat)+0.18 0.19 (sys), which smoothly connects to the H.E.S.S. spectrum in the TeV energy band. We discuss the gamma-ray emission mechanism based on multiwavelength data. The broadband data can be fit well by a model in which the gamma rays are of hadronic origin. We also consider a scenario with inverse Compton scattering of electrons as the emission mechanism of the gamma rays. Although the leptonic model predicts a harder spectrum in the Fermi-LAT energy range, the model can fit the data considering the statistical and systematic errors.

Tanaka, T.↗

NASA 5.2%-Scale Semispan High Lift Common Research Model Wind Tunnel Test at the 14- by 22-Foot Subsonic Tunnel

A wind tunnel test of the NASA 5.2%-scale Semispan High Lift Common Research Model (CRM-HL) was conducted at the 14- by 22-Foot Subsonic Tunnel (14x22) in the fall of 2022. The main purpose of the test was a model checkout before shipping it overseas. The model was shipped to Germany in the spring of 2023, and the team wanted to be sure that instrumentation in the model was working, all of the model parts fit together well, and model changes could be done smoothly, as designed while installed in a wind tunnel. Force and moment and pressure data were collected during the test, and while these data were a secondary objective, they can be used for for tunnel-to-tunnel verification of the model, and for database supplementation for the NASA CRM-HL ecosystem. The test was run from August 15, 2022 through September 8, 2022. Eight configurations were tested at Mach 0.2 and 0.26, over an alpha range from -4deg to +24deg. All of the configurations that were tested accomplished testing of all model parts. This test campaign was a unique opportunity to test a complicated model design in a wind tunnel that is less expensive to test in and has easier model access than the tunnel that it was designed to run in. The test was invaluable in providing lessons learned about building up and running the model, and the model was returned to the model manufacturer from December 2022 to February 2023 for updates to make model changes easier, to make design fixes on the model, and to do clean up work on the model.

CRM-HL↗

NASA 5.2%-Scale Semispan High Lift Common Research Model Wind Tunnel Test at the 14- by 22-Foot Subsonic Tunnel

A wind tunnel test of the NASA 5.2%-scale Semispan High Lift Common Research Model (CRM-HL) was conducted at the 14- by 22-Foot Subsonic Tunnel (14x22) in the fall of 2022. The main purpose of the test was a model checkout before shipping it overseas. The model was shipped to Germany in the spring of 2023, and the team wanted to be sure that instrumentation in the model was working, all of the model parts fit together well, and model changes could be done smoothly, as designed while installed in a wind tunnel. Force and moment and pressure data were collected during the test, and while these data were a secondary objective, they can be used for for tunnel-to-tunnel verification of the model, and for database supplementation for the NASA CRM-HL ecosystem. The test was run from August 15, 2022 through September 8, 2022. Eight configurations were tested at Mach 0.2 and 0.26, over an alpha range from -4deg to +24deg. All of the configurations that were tested accomplished testing of all model parts. This test campaign was a unique opportunity to test a complicated model design in a wind tunnel that is less expensive to test in and has easier model access than the tunnel that it was designed to run in. The test was invaluable in providing lessons learned about building up and running the model, and the model was returned to the model manufacturer from December 2022 to February 2023 for updates to make model changes easier, to make design fixes on the model, and to do clean up work on the model.

Semispan↗

Suomi NPP VIIRS Solar Diffuser Screen Transmittance Model and Its Applications

The visible infrared imaging radiometer suite on the Suomi National Polar-orbiting Partnership satellite calibrates its reflective solar bands through observations of a sunlit solar diffuser (SD) panel. Sunlight passes through a perforated plate, referred to as the SD screen, before reaching the SD. It is critical to know whether the SD screen transmittance measured prelaunch is accurate. Several factors such as misalignments of the SD panel and the measurement apparatus could lead to errors in the measured transmittance and thus adversely impact on-orbit calibration quality through the SD. We develop a mathematical model to describe the transmittance as a function of the angles that incident light makes with the SD screen, and apply the model to fit the prelaunch measured transmittance. The results reveal that the model does not reproduce the measured transmittance unless the size of the apertures in the SD screen is quite different from the design value. We attribute the difference to the orientation alignment errors for the SD panel and the measurement apparatus. We model the alignment errors and apply our transmittance model to fit the prelaunch transmittance to retrieve the "true" transmittance. To use this model correctly, we also examine the finite source size effect on the transmittance. Furthermore, we compare the product of the retrieved "true" transmittance and the prelaunch SD bidirectional reflectance distribution function (BRDF) value to the value derived from on-orbit data to determine whether the prelaunch SD BRDF value is relatively accurate. The model is significant in that it can evaluate whether the SD screen transmittance measured prelaunch is accurate and help retrieve the true transmittance from the transmittance with measurement errors, consequently resulting in a more accurate sensor data product by the same amount.

sensors↗

Program to Optimize Simulated Trajectories II (POST2) Surrogate Models for Mars Ascent Vehicle (MAV) Performance Assessment

The primary purpose of the multiPOST tool is to enable the execution of much larger sets of vehicle cases to allow for broader trade space exploration. However, this exploration is not achieved solely with the increased case throughput. The multiPOST tool is applied to carry out a Design of Experiments (DOE), which is a set of cases that have been structured to capture a maximum amount of information about the design space with minimal computational effort. The results of the DOE are then used to fit a surrogate model, ultimately enabling parametric design space exploration. The approach used for the MAV study includes both DOE and surrogate modeling. First, the primary design considerations for the vehicle were used to develop the variables and ranges for the multiPOST DOE. The final set of DOE variables were carefully selected in order to capture the desired vehicle trades and take into account any special considerations for surrogate modeling. Next, the DOE sets were executed through multiPOST. Following successful completion of the DOE cases, a manual verification trial was performed. The trial involved randomly selecting cases from the DOE set and running them by hand. The results from the human analyst's run and multiPOST were then compared to ensure that the automated runs were being executed properly. Completion of the verification trials was then followed by surrogate model fitting. After fits to the multiPOST data were successfully created, the surrogate models were used as a stand-in for POST2 to carry out the desired MAV trades. Using the surrogate models in lieu of POST2 allowed for visualization of vehicle sensitivities to the input variables as well as rapid evaluation of vehicle performance. Although the models introduce some error into the output of the trade study, they were very effective at identifying areas of interest within the trade space for further refinement by human analysts. The next section will cover all of the ground rules and assumptions associated with DOE setup and multiPOST execution. Section 3.1 gives the final DOE variables and ranges, while section 3.2 addresses the POST2 specific assumptions. The results of the verification trials are given in section 4. Section 5 gives the surrogate model fitting results, including the goodness-of-fit metrics for each fit. Finally, the MAV specific results are discussed in section 6.

Zwack, M. R.↗

Analyses of Cometary Silicate Crystals: DDA Spectral Modeling of Forsterite

Comets are the Solar System's deep freezers of gases, ices, and particulates that were present in the outer protoplanetary disk. Where comet nuclei accreted was so cold that CO ice (approximately 50K) and other supervolatile ices like ethane (C2H2) were preserved. However, comets also accreted high temperature minerals: silicate crystals that either condensed (greater than or equal to 1400 K) or that were annealed from amorphous (glassy) silicates (greater than 850-1000 K). By their rarity in the interstellar medium, cometary crystalline silicates are thought to be grains that formed in the inner disk and were then radially transported out to the cold and ice-rich regimes near Neptune. The questions that comets can potentially address are: How fast, how far, and over what duration were crystals that formed in the inner disk transported out to the comet-forming region(s)? In comets, the mass fractions of silicates that are crystalline, f_cryst, translate to benchmarks for protoplanetary disk radial transport models. The infamous comet Hale-Bopp has crystalline fractions of over 55%. The values for cometary crystalline mass fractions, however, are derived assuming that the mineralogy assessed for the submicron to micron-sized portion of the size distribution represents the compositional makeup of all larger grains in the coma. Models for fitting cometary SEDs make this assumption because models can only fit the observed features with submicron to micron-sized discrete crystals. On the other hand, larger (0.1-100 micrometer radii) porous grains composed of amorphous silicates and amorphous carbon can be easily computed with mixed medium theory wherein vacuum mixed into a spherical particle mimics a porous aggregate. If crystalline silicates are mixed in, the models completely fail to match the observations. Moreover, models for a size distribution of discrete crystalline forsterite grains commonly employs the CDE computational method for ellipsoidal platelets (c:a:b=8.14x8.14xl in shape with geometrical factors of x:y:z=1:1:10, Fabian et al. 2001; Harker et al. 2007). Alternatively, models for forsterite employ statistical methods like the Distribution of Hollow Spheres (Min et al. 2008; Oliveira et al. 2011) or Gaussian Random Spheres (GRS) or RGF (Gielen et al. 200S). Pancakes, hollow spheres, or GRS shapes similar to wheat sheaf crystal habit (e.g., Volten et al. 2001; Veihelmann et al. 2006), however, do not have the sharp edges, flat faces, and vertices seen in images of cometary crystals in interplanetary dust particles (IDPs) or in Stardust samples. Cometary forsterite crystals often have equant or tabular crystal habit (J. Bradley). To simulate cometary crystals, we have computed absorption efficiencies of forsterite using the Discrete Dipole Approximation (DDA) DDSCAT code on NAS supercomputers. We compute thermal models that employ a size distribution of discrete irregularly shaped forsterite crystals (nonspherical shapes with faces and vertices) to explore how crystal shape affects the shape and wavelength positions of the forsterite spectral features and to explore whether cometary crystal shapes support either condensation or annealing scenarios (Lindsay et al. 2012a, b). We find forsterite crystal shapes that best-fit comet Hale-Bopp are tetrahedron, bricks or brick platelets, essentially equant or tabular (Lindsay et al. 2012a,b), commensurate with high temperature condensation experiments (Kobatake et al. 2008). We also have computed porous aggregates with crystal monomers and find that the crystal resonances are amplified. i.e., the crystalline fraction is lower in the aggregate than is derived by fitting a linear mix of spectral features from discrete subcomponents, and the crystal resonances 'appear' to be from larger crystals (Wooden et al. 2012). These results may indicate that the crystalline mass fraction in comets with comae dominated by aggregates may be lower than deduced by popular methods that only emoy ensembles of discrete crystals.

Wooden, Diane↗

The p-wave upper mantle structure beneath an active spreading centre - The Gulf of California

Over 1400 seismograms of earthquakes in Mexico are analyzed and data sets for the travel time, apparent phase velocity, and relative amplitude information are utilized to produce a tightly constrained, detailed model for depths to 900 km beneath an active oceanic ridge region, the Gulf of California. The data are combined by first inverting the travel times, perturbing that model to fit the p-delta data, and then performing trial and error synthetic seismogram modelling to fit the short-period waveforms. The final model satisfies all three data sets. The ridge model is similar to existing upper mantle models for shield, tectonic-continental, and arc-trench regimes below 400 km, but differs significantly in the upper 350 km. Ridge model velocities are very low in this depth range; the model 'catches up' with the others with a very large velocity gradient from 225 to 390 km.

Walck, M. C.↗

Wilkinson Microwave Anisotropy Probe (WMAP) First Year Observations: TE Polarization

The Wilkinson Microwave Anisotropy Probe (WMAP) has mapped the full sky in Stokes I, Q, and U parameters at frequencies 23, 33, 41, 61, and 94 GHz. We detect correlations between the temperature and polarization maps significant at more than 10 standard deviations. The correlations are inconsistent with instrument noise and are significantly larger than the upper limits established for potential systematic errors. The correlations are present in all WAMP frequency bands with similar amplitude from 23 to 94 GHz, and are consistent with a superposition of a CMB signal with a weak foreground. The fitted CMB component is robust against different data combinations and fitting techniques. On small angular scales (theta less than 5 deg), the WMAP data show the temperature-polarization correlation expected from adiabatic perturbations in the temperature power spectrum. The data for l greater than 20 agree well with the signal predicted solely from the temperature power spectra, with no additional free parameters. We detect excess power on large angular scales (theta greater than 10 deg) compared to predictions based on the temperature power spectra alone. The excess power is well described by reionization at redshift 11 is less than z(sub r) is less than 30 at 95% confidence, depending on the ionization history. A model-independent fit to reionization optical depth yields results consistent with the best-fit ACDM model, with best fit value t = 0.17 +/- 0.04 at 68% confidence, including systematic and foreground uncertainties. This value is larger than expected given the detection of a Gunn-Peterson trough in the absorption spectra of distant quasars, and implies that the universe has a complex ionization history: WMAP has detected the signal from an early epoch of reionization.

Kogut, A.↗

Model Evaluation of Methods for Estimating Surface Emissions and Chemical Lifetimes from Satellite Data

Column densities from satellite retrievals can provide valuable information for estimating emissions and chemical lifetimes objectively across the globe. To better understand the uncertainties associated with these estimates, we test four methods using simulated column densities from a point source: a box model approach, a 2D Gaussian fit, an Inverse Radius fit and an Exponentially-Modified Gaussian fit. The model results were simulated using the WRF and CAMx models for the year 2005, for a single point source outside Atlanta in Georgia, USA with specified emissions and three chemical scenarios: no chemical reactions, 12 h chemical lifetime and 1 h chemical lifetime. No other sources were included in the simulations. We find that the box model provides reliable estimates irrespective of plume speed and plume direction, if the plume speed and the chemical lifetime are known accurately. The 2D Gaussian fit was found to be sensitive to plume speed and direction, and requires omnidirectional dispersion in order to have a decent fit. However, the 2D Gaussian fit is only an approximate fit to the data, and the discrepancies mean that the results are dependent on the geographical domain used for the optimization. An Inverse Radius fit is introduced to correct this issue, which is found to provide improved emissions and lifetime estimates. The Exponentially-Modified Gaussian fit also gave improved estimates. It is however dependent on accurate plume rotation such that reported chemical lifetimes with this method could be significantly underestimated.

Emission inventory↗

An Occupational Performance Test Validation Program for Fire Fighters at the Kennedy Space Center

We evaluated performance of a modified Combat Task Test (CTT) and of standard fitness tests in 20 male subjects to assess the prediction of occupational performance standards for Kennedy Space Center fire fighters. The CTT consisted of stair-climbing, a chopping simulation, and a victim rescue simulation. Average CTT performance time was 3.61 +/- 0.25 min (SEM) and all CTT tasks required 93% to 97% maximal heart rate. By using scores from the standard fitness tests, a multiple linear regression model was fitted to each parameter: the stairclimb (r(exp 2) = .905, P less than .05), the chopping performance time (r(exp 2) = .582, P less than .05), the victim rescue time (r(exp 2) = .218, P = not significant), and the total performance time (r(exp 2) = .769, P less than .05). Treadmill time was the predominant variable, being the major predictor in two of four models. These results indicated that standardized fitness tests can predict performance on some CTT tasks and that test predictors were amenable to exercise training.

Schonfeld, Brian R.↗

A cumulus cloud field observed by Landsat Thematic Mapper

The development of a spatial coherence scene model which is to be utilized to determine cloud properties from TM data is described. The observed radiances are modeled in terms of ocean and cloud spectra, the cloud fraction, and a geometric factor. Consideration is given to saturation effects and the need to constrain the model. The conjugate gradient algorithm is utilized to fit the model. A one-dimensional simulation was performed in order to evaluate the model; it is observed that the model provides good fit.

Hoffman, Ross N.↗

The computation of generalized cross-validation functions through householder tridiagonalization with applications to the fitting of interaction spline models

An efficient algorithm for computing the generalized cross-validation function for the general cross-validated regularization/smoothing problem is provided. This algorithm is appropriate for problems where no natural structure is available, and the regularization/smoothing problem is solved (exactly) in a reproducing kernel Hilbert space. It is particularly appropriate for certain multivariate smoothing problems with irregularly spaced data, and certain remote sensing problems, such as those that occur in meteorology, where the sensors are arranged irregularly. The algorithm is applied to the fitting of interaction spline models with irregularly spaced data and two smoothing parameters; favorable timing results are presented. The algorithm may be extended to the computation of certain generalized maximum likelihood (GML) functions. Application of the GML algorithm to a problem in numerical weather forecasting, and to a broad class of hypothesis testing problems, is noted.

Gu, Chong↗

A light synthesis study of W Ursae Majoris

A common set of Roche model parameters produces an accurate fit to I, V, and B data for W Ursae Majoris. The R data are defective. Two pairs of cool photospheric starspots are adopted in producing the fit. The model also adopts the cross-correlation radial velocity obtained by McLean and satisfactorily eliminates evidence, cited in the literature, for a third body in the system. Changing starspot longitudes, while maintaining fixed angular diameter, latitude, and temperature contrast from the adjacent photosphere, can simulate all of the types of light curve instability recorded in historical W Ursae Majoris light curves. Although the theoretical curve accurately fits primary minimum in U, the theoretical curve is too shallow at secondary minimum. A hot secondary explanation of W-type light curves, rather than starspots on an otherwise barotropic photosphere is argued.

Linnell, Albert P.↗

HEAO 1 A-2 low-energy detector X-ray spectra of the Lupus Loop and SN 1006

The Lupus Loop and SN 1006 were observed by the A-2 low-energy detector proportional counters on the HEAO 1 satellite as part of the all-sky survey. As a result of a major advance in understanding of detector response and background accurate analysis of the data has become possible. Soft X-ray spectra for both supernova remnants were constructed from the PHA data taken during the scanning observations. Single-temperature and two-temperature Raymond-Smith models were fitted to the observed spectra. In addition, power-law and power-law plus one-temperature models were fitted to the spectrum of SN 1006. Only two-component models provide an adequate description for both Lupus Loop and SN 1006 spectra. The temperatures, column densities, and emission measures are significantly more accurate than previous results.

Leahy, D. A.↗

An Improved Cryosat-2 Sea Ice Freeboard Retrieval Algorithm Through the Use of Waveform Fitting

We develop an empirical model capable of simulating the mean echo power cross product of CryoSat-2 SAR and SAR In mode waveforms over sea ice covered regions. The model simulations are used to show the importance of variations in the radar backscatter coefficient with incidence angle and surface roughness for the retrieval of surfaceelevation of both sea ice floes and leads. The numerical model is used to fit CryoSat-2 waveforms to enable retrieval of surface elevation through the use of look-up tables and a bounded trust region Newton least squares fitting approach. The use of a model to fit returns from sea ice regions offers advantages over currently used threshold retrackingmethods which are here shown to be sensitive to the combined effect of bandwidth limited range resolution and surface roughness variations. Laxon et al. (2013) have compared ice thickness results from CryoSat-2 and IceBridge, and found good agreement, however consistent assumptions about the snow depth and density of sea ice werenot used in the comparisons. To address this issue, we directly compare ice freeboard and thickness retrievals from the waveform fitting and threshold tracker methods of CryoSat-2 to Operation IceBridge data using a consistent set of parameterizations. For three IceBridge campaign periods from March 20112013, mean differences (CryoSat-2 IceBridge) of 0.144m and 1.351m are respectively found between the freeboard and thickness retrievals using a 50 sea ice floe threshold retracker, while mean differences of 0.019m and 0.182m are found when using the waveform fitting method. This suggests the waveform fitting technique is capable of better reconciling the seaice thickness data record from laser and radar altimetry data sets through the usage of consistent physical assumptions.

CryoSat-2↗

Quantiles, parametric-select density estimation, and bi-information parameter estimators

A quantile-based approach to statistical analysis and probability modeling of data is presented which formulates statistical inference problems as functional inference problems in which the parameters to be estimated are density functions. Density estimators can be non-parametric (computed independently of model identified) or parametric-select (approximated by finite parametric models that can provide standard models whose fit can be tested). Exponential models and autoregressive models are approximating densities which can be justified as maximum entropy for respectively the entropy of a probability density and the entropy of a quantile density. Applications of these ideas are outlined to the problems of modeling: (1) univariate data; (2) bivariate data and tests for independence; and (3) two samples and likelihood ratios. It is proposed that bi-information estimation of a density function can be developed by analogy to the problem of identification of regression models.

Parzen, E.↗