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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2

The Thermal and Kinematic Sunyaev–Zeldovich Effect in Galaxy Clusters and Filaments Using Multifrequency Temperature Maps of the Cosmic Microwave Background A399–A401 Cluster Pair Case Study

We present a multifrequency and multi-instrument methodology to study the physical properties of galaxy clusters and cosmic filaments using cosmic microwave background observations. Our approach enables simultaneous measurement of both the thermal (tSZ) and kinematic Sunyaev–Zeldovich (kSZ) effects, incorporates relativistic corrections, and models astrophysical foregrounds such as thermal dust emission. We do this by jointly fitting a single physical model across multiple maps from multiple instruments at different frequencies, rather than fitting a model to a single Compton-y map. We demonstrate the success of this method by fitting the A399–A401 galaxy cluster pair and filament system using archival data from the Planck satellite and new, targeted deep data from the Atacama Cosmology Telescope, covering 11 different frequencies over 14 maps from 30 GHz to 545 GHz. Our tSZ results are consistent with previous work using Compton-y maps. We measure the line-of-sight peculiar velocities of the cluster–filament system using the kSZ effect and find statistical uncertainties on individual cluster peculiar velocities of ≲600 km s −1 , which are competitive with current state-of-the-art measurements. Additionally, we measure the optical depth of the filament component with a signal-to-noise of 8.5σ and reveal hints of its morphology. This modular approach is well-suited for application to future instruments across a wide range of millimeter and submillimeter wavebands.

Ajay S Gill↗

Neurosymbolic Hybrid Approach to Driver Collision Warning

There are two main algorithmic approaches to autonomous driving systems: (1) An end-to-end system in which a single deep neural network learns to map sensory input directly into appropriate warning and driving responses. (2) A mediated hybrid recognition system in which a system is created by combining independent modules that detect each semantic feature. While some researchers believe that deep learning can solve any problem, others believe that a more engineered and symbolic approach is needed to cope with complex environments with less data. Deep learning alone has achieved state-of-the-art results in many areas, from complex gameplay to predicting protein structures. In particular, in image classification and recognition, deep learning models have achieved accuracies as high as humans. But sometimes it can be very difficult to debug if the deep learning model doesn't work. Deep learning models can be vulnerable and are very sensitive to changes in data distribution. Generalization can be problematic. It's usually hard to prove why it works or doesn't. Deep learning models can also be vulnerable to adversarial attacks. Here, we combine deep learning-based object recognition and tracking with an adaptive neurosymbolic network agent, called the Non-Axiomatic Reasoning System (NARS), that can adapt to its environment by building concepts based on perceptual sequences. We achieved an improved intersection-over-union (IOU) object recognition performance of 0.65 in the adaptive retraining model compared to IOU 0.31 in the COCO data pre-trained model. We improved the object detection limits using RADAR sensors in a simulated environment, and demonstrated the weaving car detection capability by combining deep learning-based object detection and tracking with a neurosymbolic model.

Wang, Pei↗

Measurements and Computational Analysis of the Turbulent Corner Flow on the NASA Juncture-Flow Model with a Symmetric Wing

The NASA Juncture Flow Experiment is designed to acquire high-quality flowfield data deep in the corner of a wing-fuselage junction for the purpose of computational fluid dynamics (CFD) validation and turbulence model improvement. This report presents and discusses the results of a recent experiment with the Juncture Flow Model in the NASA Langley 14- by 22-Foot Subsonic Tunnel. The main objective of the test was to expand the existing juncture-flow dataset with a symmetric wing case that displays fully attached, incipient separation, and separated flow in the corner of the wing-fuselage junction, depending on the model angle of incidence. Laser Doppler velocimetry (LDV) measurements were made at three model angles of incidence (0° : fully attached, 1° : incipient separation, and 5° : separated flow) and for each angle, mean-flow and Reynolds-stress data were obtained on the fuselage and at several locations along the corner of the wing-fuselage junction. Supporting measurements were made during the test campaign and include model and tunnel wall static pressures, tunnel wall boundary-layer profiles, oil-flow visualizations, and laser-based measurements of the as-built model geometry and model position in the test section. A companion set of Reynolds-averaged Navier-Stokes (RANS) CFD simulations were also performed and those results were used to support the discussion of the experimental test results.

Juncture Flow↗

Measurements and Computations of the Turbulent Corner Flow on the NASA Juncture-Flow Model with a Symmetric Wing

The NASA Juncture Flow experiment is designed to acquire high-quality flowfield data deep in the corner of a wing-fuselage junction specifically for the purpose of computational fluid dynamics (CFD) validation and turbulence model improvement. This paper will present and discuss the results of a recent experiment with the juncture-flow model in the NASA Langley 14- by 22-Foot Subsonic Tunnel. The main objective of that test was to expand the existing juncture-flow dataset with a symmetric wing case that displays fully attached, incipient separation, and separated flow in the corner of the wing-fuselage junction, depending on the model pitch angle. Laser Doppler velocimetry (LDV) measurements were made at three model pitch angles (0 deg: fully attached, 1 deg: incipient separation, and 5 deg: separated flow) and for each one, mean-flow and Reynolds-stress data was obtained on the fuselage and at several streamwise locations along the corner of the wing-fuselage junction. Supporting measurements were made during the test campaign and included model and tunnel wall static pressures, tunnel wall and ceiling boundary-layer rake data, oil-flow visualizations, and laser-based measurements of the as-built model geometry and model position in the test section. Comparisons between the experimental data and Reynolds averaged Navier-Stokes CFD results will also be presented and discussed.

Juncture Flow↗

Measurements and Computations of the Turbulent Corner Flow on the NASA Juncture-Flow Model with a Symmetric Wing

The NASA Juncture Flow experiment is designed to acquire high-quality flowfield data deep in the corner of a wing-fuselage junction specifically for the purpose of computational fluid dynamics (CFD) validation and turbulence model improvement. This paper will present and discuss the results of a recent experiment with the juncture-flow model in the NASA Langley 14- by 22-Foot Subsonic Tunnel. The main objective of that test was to expand the existing juncture-flow dataset with a symmetric wing case that displays fully attached, incipient separation, and separated flow in the corner of the wing-fuselage junction, depending on the model pitch angle. Laser Doppler velocimetry (LDV) measurements were made at three model pitch angles (0 deg: fully attached, 1 deg: incipient separation, and 5 deg: separated flow) and for each one, mean-flow and Reynolds-stress data was obtained on the fuselage and at several streamwise locations along the corner of the wing-fuselage junction. Supporting measurements were made during the test campaign and included model and tunnel wall static pressures, tunnel wall and ceiling boundary-layer rake data, oil-flow visualizations, and laser-based measurements of the as-built model geometry and model position in the test section. Comparisons between the experimental data and Reynolds averaged Navier-Stokes CFD results will also be presented and discussed.

Juncture Flow↗

Measurements and Computations of the Turbulent Corner Flow on the NASA Juncture-Flow Model with a Symmetric Wing

The NASA Juncture Flow experiment is designed to acquire high-quality flowfield data deep in the corner of a wing-fuselage junction specifically for the purpose of computational fluid dynamics (CFD) validation and turbulence model improvement. This paper presents and discusses the results of a recent experiment with the juncture-flow model in the NASA Langley 14- by 22-Foot Subsonic Tunnel. The main objective of the test was to expand the existing juncture-flow dataset with a symmetric wing case that displays fully attached, incipient separation, and separated flow in the corner of the wing-fuselage junction, depending on the model angle of incidence. Laser Doppler velocimetry (LDV) measurements were made at three model angles of incidence (0 deg: fully attached, 1 deg: incipient separation, and 5 deg: separated flow) and for each one, mean-flow and Reynolds-stress data were obtained on the fuselage and at several streamwise locations along the corner of the wing-fuselage junction. Supporting measurements were made during the test campaign and included model and tunnel wall static pressures, tunnel wall and ceiling boundary-layer rake data, oil-flow visualizations, and laser-based measurements of the as-built model geometry and model position in the test section. Comparisons between the experimental data on the test article and Reynolds-averaged Navier-Stokes CFD results are presented and discussed.

Juncture Flow↗

Table-driven configuration and formatting of telemetry data in the Deep Space Network

With a restructured software architecture for telemetry system control and data processing, the NASA/Deep Space Network (DSN) has substantially improved its ability to accommodate a wide variety of spacecraft in an era of 'better, faster, cheaper'. In the new architecture, the permanent software implements all capabilities needed by any system user, and text tables specify how these capabilities are to be used for each spacecraft. Most changes can now be made rapidly, outside of the traditional software development cycle. The system can be updated to support a new spacecraft through table changes rather than software changes, reducing the implementation, test, and delivery cycle for such a change from three months to three weeks. The mechanical separation of the text table files from the program software, with tables only loaded into memory when that mission is being supported, dramatically reduces the level of regression testing required. The format of each table is a different compromise between ease of human interpretation, efficiency of computer interpretation, and flexibility.

Manning, Evan↗

A Determination of the Intergalactic Redshift Dependent UV-Optical-NIR Photon Density Using Deep Galaxy Survey Data and the Gamma-Ray Opacity of the Universe

We calculate the intensity and photon spectrum of the intergalactic background light (IBL) as a function of red shift using an approach based on observational data obtained at in different wavelength bands from local to deep galaxy surveys. Our empirically based approach allows us, for the firs.t time, to obtain a completely model independent determination of the IBL and to quantify its uncertainties. Using our results on the IBL, we then place upper and lower limits on the opacity of the universe to gamma-rays, independent of previous constraints.

Stecker, Floyd W.↗

A Determination of the Intergalactic Redshift Dependent UV-Optical-NIR Photon Density Using Deep Galaxy Survey Data and the Gamma-ray Opacity of the Universe

We calculate the intensity and photon spectrum of the intergalactic background light (IBL) as a function of redshift using an approach based on observational data obtained in many different wavelength bands from local to deep galaxy surveys. This allows us to obtain an empirical determination of the IBL and to quantify its observationally based uncertainties. Using our results on the IBL, we then place 68% confidence upper and lower limits on the opacity of the universe to gamma-rays, free of the theoretical assumptions that were needed for past calculations. We compare our results with measurements of the extragalactic background light and upper limits obtained from observations made by the Fermi Gamma-ray Space Telescope.

Stecker, Floyd W.↗

A command and data subsystem for deep space exploration based on the RCA 1802 microprocessor in a distributed configuration

The Command and Data Subsystem (CDS) is an RCA 1802microprocessor based subsystem that acts as the central nervous system for the Galileo Orbiter Spacecraft. All communication between the ground and spacecraft flows through the CDS. The CDS also distributes commands in real time, algorithmetrically expanded from a data base loaded from the ground and in response to spacecraft alarms. The distributed microprocessor system is configured as a redundant set of hardware with three microprocessors on each half. The microprocessors are surrounded by a group of special purpose hardware components which greatly enhance the ability of the software to perform its task. It is shown how the software architecture makes a distributed system of six microprocessors appear to each user as a single virtual machine, and collectively as a set of cooperating virtual machines that prevent the simultaneous presence of the several users from interfering destructively with each other.

Thomas, J. S.↗

New Measurements of the Cosmic Infrared Background Fluctuations in Deep SpitzerllRAC Survey Data and their Cosmological Implications

We extend the previous measurements of CIB fluctuations to angular scales of less than or equal to 1 degree new data obtained in the course of the 2,000+ hour Spitzer Extended Deep Survey. Two fields with completed observations of approximately equal to 12 hr/pixel are analyzed for source-subtracted CIB fluctuations at 3.6 and 4.5 micrometers. The fields, EGS and UDS, cover a total area of approximately 0.25 deg and lie at high Galactic and Ecliptic latitudes, thus minimizing cirrus and zodiacal light contributions to the fluctuations. The observations have been conducted at 3 distinct epochs separated by about 6 months. As in our previous studies, the fields were assembled using the self-calibration method which is uniquely suitable for probing faint diffuse backgrounds. The assembled fields were cleaned off the bright sources down to the low shot noise levels corresponding to AB mag approximately equal to 25, Fourier-transformed and their power spectra evaluated. The noise was estimated from the time-differenced data and subtracted from the signal isolating the fluctuations remaining above the noise levels. The power spectra of the source-subtracted fields remain identical (within the observational uncertainties) for the three epochs of observations indicating that zodiacal light contributes negligibly to the fluctuations. By comparing to the measurements for the same regions at 8 micrometers we demonstrate that Galactic cirrus cannot account for the levels of the fluctuations either. The signal appears isotropically distributed on the sky as required by its origin in the CIB fluctuations. This measurement thus extends our earlier results to the important range of sub-degree scales. We find that the CIB fluctuations continue to diverge to more than 10 times those of known galaxy populations on angular scales out to less than or equal to 1 degree. The low shot noise levels remaining in the diffuse maps indicate that the large scale fluctuations arise from spatial clustering of faint sources well within the confusion noise. The spatial spectrum of these fluctuations is in reasonable agreement with simple fitting assuming that they originate in early populations spatially distributed according to the standard cosmological model (ACDM) at epochs coinciding with the first stars era. The alternative to this identification would require a new population never observed before, nor expected on theoretical grounds, but if true this would represent an important discovery in its own right.

Kashlinsky, A.↗

Application of Non-Coherent Doppler Data Types for Deep Space Navigation

improvements in computational capability and DSN technology have renewed interest in examining the possibility of using one-way Doppler data alone to navigate interplanetary spacecraft. The one-way data can be formulated as the standard difference-count Doppler or as phase measurements, and the data can be received at a single station or differenced if obtained simultaneously at two stations. A covariance analysis is performed which analyzes the accuracy obtainable by combinations of one-way Doppler data and compared with similar results using standard tow-way Doppler and range. The sample interplanetary trajectory used was that of the Mars Pathfinder mission to Mars. It is shown that differenced one-way data is capable of determining the angular position of the spacecraft to fairly high accuracy, but has relatively poor sensitivity to the range. When combined with single station data, the position dispersions are roughly an order of magnitude larger in range and comparable in angular position as compared to dispersions obtained with standard data two-way types. It was also found that the phase formulation is less sensitive to data weight variations and data coverage than the differenced-count Doppler formulation.

Deep↗

Comparison of earth-based radio metric data strategies for deep space navigation

Spacecraft angular coordinates can be determined with a variety of radio tracking measurements, such as Doppler, range, and Very Long Baseline Interferometry (VLBI)-derived data types. A relatively new interferometric tracking technique under development is Connected Element Interferometry (CEI), which uses a single frequency standard, distributed to two antennas spaced 10 to 100 km apart, to make highly accurate measurements of the phase-delay of incoming radio signals. The angular navigation accuracies attainable with Doppler, range, CEI, and VLBI data strategies are compared, using simple analytic models for these data types. The measurement accuracies assumed for Doppler, range, and VLBI data represent the performance expected from these systems in the Magellan and Galileo missions, while the assumed CEI data accuracy represents the anticipated performance of an experimental connected element system being constructed at the Deep Space Network's Goldstone, California complex. The results indicate that the Galileo VLBI system can deliver 20- to 25-nrad accuracy throughout the ecliptic plane. A hypothetical CEI dual-baseline sysem at Goldstone yielded accuracies in the 35- to 50-nrad range, while another hypothetical Goldstone-based system, consisting of a single CEI baseline and an X-band (8.4 GHz) Doppler system, produced accuracies of 25 to 100 nrad. Angular accuracies obtained from Doppler and range were found to be highly dependent upon the sensitivity of earth-spacecraft differential acceleration to small changes in geocentric spacecraft position.

Thurman, Sam W.↗

(abstract) Application of Non-coherent Data Types for Deep Space Navigation

Several options are being examined to reduce the costs of spacecraft and deep space missions. One such option is to fly spacecraft in a non-coherent mode, that is, the spacecraft does not carry a transponder and cannot coherently return a Doppler signal. Historically, such one-way data has not been used as the sole data type due to the instability of the onboard oscillator, the use of S-band frequencies, and the corresponding larger error sources which could not be modeled. However, with the advent of high-speed work stations and more sophisticated modeling ability, the possibility of using one-way data is being re-examined. This paper addresses the navigation performance of various one-way data types for use in interplanetary missions.

deep space navigation non-coherent data spacecraft↗