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At least 595 records · Page 33

Quantitative determination of stratospheric aerosol characteristics

The author has identified the following significant results. In the S192 data, a peak was apparent in the lower altitudes that was not present in the shorter wavelengths and grew with increasing wavelength beginning with band 7. For ten S192 wavelengths, the relative altitude increment was determined by knowledge of the relative position of the highest point in the scan arc. Using this scheme, results of scaling and inverting data for passes 47 and 61 were put into two models. Each result had three chart representations: (1) limb brightness measurement, (2) attenuation coefficients, and (3) ratio of the aerosol and Rayleigh coefficients to accentuate layers.

Tingey, D. L.↗

Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.

42 ENGINEERING↗

Reprint of: Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.

47 OTHER INSTRUMENTATION↗

An analysis of Skylab II S193 scatterometer data

Skylab II S193 scatterometer data for the passes of June 5, 1973, over the Gulf of Mexico and June 6, 1973, over Pacific Hurricane AVA were analyzed. These two passes were chosen since it was possible to correlate the scattering data with simultaneous measurements of the local ocean wind conditions. The S193 scatterometer measured the radar cross section of the ocean at 13.9 GHz (Ku-band) as a function of incidence angle. The S193 data of June 5, 1973, when a practically uniform wind field was present, show reasonable agreement with the Naval Research Laboratory (NRL) empirical and theoretical models. The data of June 6, 1973, are more complex, due to rapid variations in wind speeds and directions around Hurricane AVA. The NRL empirical model was interpolated to account for variation in wind heading relative to the S193 antenna pointing direction; a reasonable comparison could then be made with the corresponding S193 data of June 6, 1973.

Jordan, A. K.↗

Chorus-related electrostatic bursts at Jupiter and Saturn

Analyses of the wideband plasma wave data obtained by Voyagers 1 and 2 at Jupiter and Saturn have revealed electrostatic bursts similar to those recently discovered at earth in association with whistler-mode chorus. In all three magnetospheres the bursts are characterized by sporadic emissions near or slightly below the electron plasma frequency with bandwidths ranging from 10 percent to more than 50 percent of the center frequency. The events found at Jupiter occur in the middle magnetosphere during both the dayside as well as the early morning passes. At Saturn, the bursts occurred in the outer regions of the magnetosphere during the dayside pass. In each of the events analyzed, evidence exists for modulation of the electrostatic bursts by a low frequency wave, presumably chorus. One of the observations gained at Jupiter includes the detection of a low-frequency band at the proper frequency for chorus. Detailed waveform analysis confirms that this band does, indeed, modulate the electrostatic bursts. Based on the present understanding of the terrestrial observations it is believed that the electrostatic bursts are generated by an electron beam trapped in Landau resonance with the chorus. Previously announced in STAR as N83-37042

Reinleitner, L. A.↗

An autoranging scanning system and compatible methods of noise reduction

The autoranging scanning system discussed combines in a unique way four different methods for removing noise. The system employs a narrow-band amplifier. Other noise reduction methods make use of digital summation, convolution numbers, and the coaddition of scans. The system was designed to digitize the output of an infrared spectrometer and to record it on magnetic tape. Light passes through a mechanical light chopper and the spectrometer optics, and falls on the PbS cell to produce a signal which is amplified by the first preamplifier.

Saufley, D. C.↗

Investigation of the application of HCMM thermal data to snow hydrology

The author has identified the following significant results. Comparison of the thermal IR band temperatures over the rapidly melting snowcover in a number of locations in the Salt-Verde Arizona watershed by the U-2 high altitude multispectral scanner, with temperatures for these same locations measured by the corresponding HCMM pass, indicate that the U-2 temperatures are typically 5 C higher than the values analyzed from the HCMM infrared digital printout. Results tend to substantiate findings of other investigators that with the offset that has been applied to all HCMM data, the HCMM temperature values may, in fact, actually be 5 C too low. Analysis of differences between the HCMM day and night temperatures for selected snowcovered areas in the Sierra Nevada Mountains, derived from the daytime and nighttime printouts, show greater delta tau values for the sparsely vegetated higher elevations than for the lower elevation, more densely forested terrain. The differences for the 12 hour sequence are also greater in most instances than the 36 hour difference.

Barnes, J. C.↗

Seeing ghosts - Photometry of Saturn's G Ring

Saturn's faint and narrow G Ring is only visible to the eye in two Voyager images, each taken at a rather high solar phase angle of about 160 deg. In this paper we introduce a new photometric technique for averaging across multiple Voyager images, and use it to detect the G Ring at several additional viewing geometries. The resultant phase curve suggests that the G Ring is composed of dust particles obeying a very steep power-law size distribution. The dust is generally smaller than that seen in other rings, ranging down to 0.03 micron. The G Ring occupies the region between orbital radii 166,000 and 173,000 km, and has a peak somewhat closer to the inner edge. Based on these limits, we demonstrate that Voyager 2 passed through and directly sampled this ring during its 1981 encounter with Saturn. Combined analysis of additional data sets suggests that a population of larger bodies is also present in the G Ring; these bodies occupy a narrower band near the observed peak and are likely the source for the visible dust. Based on some preliminary dynamical models, we propose that these larger bodies represent leftover debris from the collisional breakup of a small moon in Saturn's distant past.

Showalter, Mark R.↗

Radiative Heating Profiles over Ascension Island during the 2016 and 2017 Biomass Burning Seasons

Marine boundary layer clouds, including the transition from stratocumulus to cumulus, are poorly represented in numerical weather prediction and general circulation models. In many cases, the complex physical relationships between cloud morphology and the environmental conditions in which marine boundary layer clouds exist are not well understood. Such uncertainties arise in the presence of biomass burning carbonaceous aerosol, as is the case over the southeast Atlantic Ocean, where it is likely that the absorbing and heating properties of these aerosols modify the microphysical composition and macrophysical arrangement of marine stratocumulus and trade cumulus. The deployment of the Atmospheric Radiation Measurement Mobile Facility #1 (AMF1) in support of LASIC (Layered Atlantic Smoke Interactions with Clouds) provided a unique opportunity to observe thermodynamic, cloud and aerosol properties during two consecutive biomass burning seasons from July through October of 2016 and 2017 over Ascension Island (7.96 S, 14.35 W). These observations in conjunction with radiation transfer modeling were used to assess the impact of biomass burning carbonaceous aerosol plumes as they passed over the site.Thermodynamic profiles were generated using a combination of radiosonde data and thermodynamic profilers to provide high temporal resolution profiles of quantities that are important for cloud development, such as CAPE and CIN. Coincident Ka-band radar and lidar profiles were used to characterize the cloud and sub-cloud structure. The resulting thermodynamic and cloud profiles are used as input forcing for the Rapid Radiative Transfer Model (RRTM) to compute radiative heating profiles over the observation site. Idealized experiments using RRTM, with and without aerosols present, are used to assess the impacts of the absorbing aerosol on the heating rate profiles.

Cumulus↗

Monitoring surface albedo change with Landsat

A pronounced decrease of the surface albedo (reflectivity) has been observed in an area in the Northern Sinai, fenced-in in the summer of 1974. Analysis of the Landsat Multispectral Scanner System digital data from an April 1977 pass indicates a reduction in the albedo in the exclosure by 13%, as compared to the outside, which continues to be subjected to overgrazing and anthropogenic pressures. The reduction of reflectivity is approximately the same in all the spectral bands, and is therefore attributable to accumulation of dead plants and plant debris, and not directly to live vegetation.

Otterman, J.↗

Radar Interferometer for Topographic Mapping of Glaciers and Ice Sheets

A report discusses Ka-band (35-GHz) radar for mapping the surface topography of glaciers and ice sheets at high spatial resolution and high vertical accuracy, independent of cloud cover, with a swath-width of 70 km. The system is a single- pass, single-platform interferometric synthetic aperture radar (InSAR) with an 8-mm wavelength, which minimizes snow penetration while remaining relatively impervious to atmospheric attenuation. As exhibited by the lower frequency SRTM (Shuttle Radar Topography Mission) AirSAR and GeoSAR systems, an InSAR measures topography using two antennas separated by a baseline in the cross-track direction, to view the same region on the ground. The interferometric combination of data received allows the system to resolve the pathlength difference from the illuminated area to the antennas to a fraction of a wavelength. From the interferometric phase, the height of the target area can be estimated. This means an InSAR system is capable of providing not only the position of each image point in along-track and slant range as with a traditional SAR but also the height of that point through interferometry. Although the evolution of InSAR to a millimeter-wave center frequency maximizes the interferometric accuracy from a given baseline length, the high frequency also creates a fundamental problem of swath coverage versus signal-to-noise ratio. While the length of SAR antennas is typically fixed by mass and stowage or deployment constraints, the width is constrained by the desired illuminated swath width. As the across-track beam width which sets the swath size is proportional to the wavelength, a fixed swath size equates to a smaller antenna as the frequency is increased. This loss of antenna size reduces the two-way antenna gain to the second power, drastically reducing the signal-to-noise ratio of the SAR system. This fundamental constraint of high-frequency SAR systems is addressed by applying digital beam-forming (DBF) techniques to synthesize multiple simultaneous receive beams in elevation while maintaining a broad transmit illumination. Through this technique, a high antenna gain on receive is preserved, thereby reducing the required transmit power and thus enabling high-frequency SARs and high-precision InSAR from a single spacecraft.

Moller, Delwyn K.↗

Classification Of Land Cover From Airborne MSS Data

Method for processing images of rural uplands produced by airborne multispectral scanner (MSS), semiautomatically classifies types of land cover, and involves selection of wavelength bands, radiometric calibration, correction for effects of scan angle and atmosphere, training, and assessment of accuracy. Basic version involves classification of each picture element according to spectrum. Augmented with five refinements to increase accuracy: per-field sampling; low-pass filtering; image texture; prior probabilities; and imagery from two dates.

Curran, Paul J.↗

Evidence for the interaction of large scale magnetic structures in solar flares

By modeling the observed vertical magnetic field of an active region AR 2372 by the potential field of an ensemble of magnetic dipoles, the likely location of the separatrices, surfaces that separates cells of different field line connectivities, and of the separator which is the intersection of the separatrices, is derived. Four of the five off-band H-alpha kernels of a flare that occurred less than 20 minutes before obtaining the magnetogram are shown to have taken place near or at the separatrices. These H-alpha kernels are connected by field lines that pass near the separator. This indicates that the flare may have resulted from the interaction in the separator region of large scale magnetic structures.

Mandrini, C. H.↗

C/NOFS Satellite Electric Field and Plasma Density Observations of Plasma Instabilities Below the Equatorial F-Peak -- Evidence for Approximately 500 km-Scale Spread-F "Precursor" Waves Driven by Zonal Shear Flow and km-Scale, Narrow-Banded Irregularities

As solar activity has increased, the ionosphere F-peak has been elevated on numerous occasions above the C/NOFS satellite perigee of 400km. In particular, during the month of April, 2011, the satellite consistently journeyed below the F-peak whenever the orbit was in the region of the South Atlantic anomaly after sunset. During these passes, data from the electric field and plasma density probes on the satellite have revealed two types of instabilities which had not previously been observed in the C/NOFS data set (to our knowledge): The first is evidence for 400-500km-scale bottomside "undulations" that appear in the density and electric field data. In one case, these large scale waves are associated with a strong shear in the zonal E x B flow, as evidenced by variations in the meridional (outward) electric fields observed above and below the F-peak. These undulations are devoid of smaller scale structures in the early evening, yet appear at later local times along the same orbit associated with fully-developed spread-F with smaller scale structures. This suggests that they may be precursor waves for spread-F, driven by a collisional shear instability, following ideas advanced previously by researchers using data from the Jicamarca radar. A second new result (for C/NOFS) is the appearance of km-scale irregularities that are a common feature in the electric field and plasma density data that also appear when the satellite is below the F -peak at night. The vector electric field instrument on C/NOFS clearly shows that the electric field component of these waves is strongest in the zonal direction. These waves are strongly correlated with simultaneous observations of plasma density oscillations and appear both with, and without, evidence of larger-scale spread-F depletions. These km-scale, quasi-coherent waves strongly resemble the bottomside, sinusoidal irregularities reported in the Atmosphere Explorer satellite data set by Valladares et al. [JGR, 88, 8025, 1983]. We interpret these new observations in terms of fundamental plasma instabilities associated with the unstable, nighttime equatorial ionosphere.

Pfaff, R.↗

The Ecosystems SAR (EcoSAR) an Airborne P-band Polarimetric InSAR for the Measurement of Vegetation Structure, Biomass and Permafrost

EcoSAR is a new synthetic aperture radar (SAR) instrument being developed at the NASA/ Goddard Space Flight Center (GSFC) for the polarimetric and interferometric measurements of ecosystem structure and biomass. The instrument uses a phased-array beamforming architecture and supports full polarimetric measurements and single pass interferometry. This Instrument development is part of NASA's Earth Science Technology Office Instrument Incubator Program (ESTO IIP).

SAR↗

Operator evolution from the similarity renormalization group and the Magnus expansion

The Magnus expansion is an efficient alternative to solving similarity renormalization group (SRG) flow equations with high-order, memory-intensive ordinary differential equation solvers. The numerical simplifications it offers for operator evolution are particularly valuable for in-medium SRG calculations, though challenges remain for difficult problems involving intruder states. Here we test the Magnus approach in an analogous but more accessible situation, which is the free-space SRG treatment of the spurious bound states arising from a leading-order chiral effective field theory (EFT) potential with very high cutoffs. In this work, we show that the Magnus expansion passes these tests and then use the investigations as a springboard to address various aspects of operator evolution that have renewed relevance in the context of the scale and scheme dependence of nuclear processes. These aspects include SRG operator flow with band- versus block-diagonal generators, universality for chiral EFT Hamiltonians and associated operators with different regularization schemes, and the impact of factorization arising from scale separation. Implications for short-range correlations physics and the possibilities for reconciling high- and low-resolution treatments of nuclear structure and reactions are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The Dark Energy Survey: Cosmology Results with ∼1500 New High-redshift Type Ia Supernovae Using the Full 5 yr Data Set

Abstract We present cosmological constraints from the sample of Type Ia supernovae (SNe Ia) discovered and measured during the full 5 yr of the Dark Energy Survey (DES) SN program. In contrast to most previous cosmological samples, in which SNe are classified based on their spectra, we classify the DES SNe using a machine learning algorithm applied to their light curves in four photometric bands. Spectroscopic redshifts are acquired from a dedicated follow-up survey of the host galaxies. After accounting for the likelihood of each SN being an SN Ia, we find 1635 DES SNe in the redshift range 0.10 < z < 1.13 that pass quality selection criteria sufficient to constrain cosmological parameters. This quintuples the number of high-quality z > 0.5 SNe compared to the previous leading compilation of Pantheon+ and results in the tightest cosmological constraints achieved by any SN data set to date. To derive cosmological constraints, we combine the DES SN data with a high-quality external low-redshift sample consisting of 194 SNe Ia spanning 0.025 < z < 0.10. Using SN data alone and including systematic uncertainties, we find Ω M = 0.352 ± 0.017 in flat ΛCDM. SN data alone now require acceleration ( q 0 < 0 in ΛCDM) with over 5 σ confidence. We find ( Ω M , w ) = ( 0.264 − 0.096 + 0.074 , − 0.80 − 0.16 + 0.14 ) in flat w CDM. For flat w 0 w a CDM, we find ( Ω M , w 0 , w a ) = ( 0.495 − 0.043 + 0.033 , − 0.36 − 0.30 + 0.36 , − 8.8 − 4.5 + 3.7 ) , consistent with a constant equation of state to within ∼2 σ . Including Planck cosmic microwave background, Sloan Digital Sky Survey baryon acoustic oscillation, and DES 3 × 2pt data gives (Ω M , w ) = (0.321 ± 0.007, −0.941 ± 0.026). In all cases, dark energy is consistent with a cosmological constant to within ∼2 σ . Systematic errors on cosmological parameters are subdominant compared to statistical errors; these results thus pave the way for future photometrically classified SN analyses.

79 ASTRONOMY AND ASTROPHYSICS↗

Structural design options for the new 34 meter beam waveguide antenna

In addition to the successful network of 34 m High Efficiency antennas recently built by JPL, the Deep Space Network (DSN) is embarking on the construction of a 34 m high performance, research and development antenna with beam waveguide optics at the Venus site. The construction of this antenna presents many engineering challenges in the area of structural, mechanical, RF, and pointing system design. A set of functional and structural design requirements is outlined to guide analysts in the final configuration selection. Five design concepts are presented covering both the conventional center-fed beam optics as well as the nonconventional, by-pass beam configuration. The merits of each concept are discussed with an emphasis on obtaining a homologous design. The preliminary results of structural optimization efforts, currently in progress, are promising, indicating the feasibility of meeting, as a minimum, all X-band (8.4 GHz) requirements, with a goal towards meeting Ka-band (32 GHz) quality performance, at the present budget constraints.

Katow, S.↗