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At least 523 records · Page 29

Wind Tunnel Results of the Aerodynamic Performance of a 1/8-Scale Model of a Twin-Engine Transport with Multi-Element Wing

A wind tunnel investigation was performed in the 14- by 22-Foot Subsonic Tunnel on a pressure instrumented 1/8-scale twin-engine subsonic transport to better understand the flow physics on a multi-element wing section. The wing consisted of a part-span, triple-slotted trailing edge flap, inboard leading-edge Krueger flap and an outboard leading-edge slat. The model was instrumented with flush pressure ports at the fuselage centerline and seven spanwise wing locations. The model was tested in cruise, take-off and landing configurations at dynamic pressures and Mach numbers from 10 lbf/ft(exp 2) to 50 lbf/ft(exp 2) and 0.08 to 0.17, respectively. This resulted in corresponding Reynolds numbers of 0.8 x 10(exp 5) to 1.8 x 10(exp 6). Pressure data were collected using electronically scanned pressure devices and force and moment data were collected with a six component strain gauge balance. Results are presented for various control surface deflections over an angle-of-attack range from -4 degrees to 16 degrees and sideslip angle range from -10 degrees to 10 degrees. Longitudinal and lateral directional aerodynamic data are presented as well as chordwise pressure distributions at the seven spanwise wing locations and the fuselage centerline.

Laflin, Brenda E. Gile↗

An Ensemble Approach to Building Mercer Kernels with Prior Information

This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly dimensional feature space. we describe a new method called Mixture Density Mercer Kernels to learn kernel function directly from data, rather than using pre-defined kernels. These data adaptive kernels can encode prior knowledge in the kernel using a Bayesian formulation, thus allowing for physical information to be encoded in the model. Specifically, we demonstrate the use of the algorithm in situations with extremely small samples of data. We compare the results with existing algorithms on data from the Sloan Digital Sky Survey (SDSS) and demonstrate the method's superior performance against standard methods. The code for these experiments has been generated with the AUTOBAYES tool, which automatically generates efficient and documented C/C++ code from abstract statistical model specifications. The core of the system is a schema library which contains templates for learning and knowledge discovery algorithms like different versions of EM, or numeric optimization methods like conjugate gradient methods. The template instantiation is supported by symbolic-algebraic computations, which allows AUTOBAYES to find closed-form solutions and, where possible, to integrate them into the code.

Srivastava, Ashok N.↗

Putting Priors in Mixture Density Mercer Kernels

This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly infinite dimensional feature space. We describe a new method called Mixture Density Mercer Kernels to learn kernel function directly from data, rather than using predefined kernels. These data adaptive kernels can en- code prior knowledge in the kernel using a Bayesian formulation, thus allowing for physical information to be encoded in the model. We compare the results with existing algorithms on data from the Sloan Digital Sky Survey (SDSS). The code for these experiments has been generated with the AUTOBAYES tool, which automatically generates efficient and documented C/C++ code from abstract statistical model specifications. The core of the system is a schema library which contains template for learning and knowledge discovery algorithms like different versions of EM, or numeric optimization methods like conjugate gradient methods. The template instantiation is supported by symbolic- algebraic computations, which allows AUTOBAYES to find closed-form solutions and, where possible, to integrate them into the code. The results show that the Mixture Density Mercer-Kernel described here outperforms tree-based classification in distinguishing high-redshift galaxies from low- redshift galaxies by approximately 16% on test data, bagged trees by approximately 7%, and bagged trees built on a much larger sample of data by approximately 2%.

Srivastava, Ashok N.↗

Experimental Investigation of Rotating Stall in a Research Multistage Axial Compressor

A collection of experimental data acquired in the NASA low-speed multistage axial compressor while operated in rotating stall is presented in this paper. The compressor was instrumented with high-response wall pressure modules and a static pressure disc probe for in-flow measurement, and a split-fiber probe for simultaneous measurements of velocity magnitude and flow direction. The data acquired to-date have indicated that a single fully developed stall cell rotates about the flow annulus at 50.6% of the rotor speed. The stall phenomenon is substantially periodic at a fixed frequency of 8.29 Hz. It was determined that the rotating stall cell extends throughout the entire compressor, primarily in the axial direction. Spanwise distributions of the instantaneous absolute flow angle, axial and tangential velocity components, and static pressure acquired behind the first rotor are presented in the form of contour plots to visualize different patterns in the outer (midspan to casing) and inner (hub to mid-span) flow annuli during rotating stall. In most of the cases observed, the rotating stall started with a single cell. On occasion, rotating stall started with two emerging stall cells. The root cause of the variable stall cell count is unknown, but is not attributed to operating procedures.

Lepicovsky, Jan↗

Remote-sensing based technique to account for sub-grid scale variability of land surface properties

A method has been presented for the representation of sub-grid scale variability of surface properties within a land surface processes model. The method uses remotely-sensed data to directly or indirectly estimate probability density functions (PDF's) or key surface variables. Application of this technique in a coupled land surface-atmosphere model requires only grid-scale values of the variables of interest, obtained from low-resolution satellite imagery or surface/remote sensing data assimilation. The PDF's of each controlling surface property are superimposed on the respective grid-scale values to simulate sub-grid scale heterogeneity. Sensitivity studies will be carried out to ascertain the relative importance of the heterogeneity of several variables, and the degree to which non-linear property-process interactions impact large-scale fluxes.

Crosson, William L.↗

"Sensor Web Evolution - Webs of Webs for NASA Science - Focus on small Uninhabited Aerial Systems (sUAS)"

This paper will describe the evolution of information collection, derivation and delivery mechanisms in webs of NASA sensor webs, with a focus on recent advancements in small Uninhabited Aerial Systems (sUAS). I will discuss the movement to "Fog Computing", also known as Edge Computing. Fog Computing facilitates the distribution of common operations and networking between edge devices and cloud computing facilities, optimizing the production of actionable intelligence. Initially, sUASs utilized onboard data collection as standard, with minimal data downloaded directly. Information products were derived in conventional computational environments, generally desk top computers, and information products made available to the Science Community in weeks or months. With the increased availability, and increasingly lower costs, of beyond line of sight (BLOS) satellite based communication, transmission rates and data volumes increased, and processing migrated to Cloud based services. Contemporary sUASs are moving some of that information product derivation to on vehicle services, and are creating a distributed Cloud/Fog environment. I will describe the technological advances that have made this possible, including low power multi-core Central Processing Units (CPU), and, more recently, the availability of high end Graphical Processing Units (GPU) that consume only a few watts. Intelligent system software, leveraging these hardware advances, finally allows for information product generation on-board, rather than simple data collection. Additionally, intelligent flight control systems now support mutual vehicle to vehicle collaboration, allowing sUASs to create ad-hoc sensor webs on demand, as required. Also discussed will be the lessons learned by the Authors' development of data systems for NASA's large High Altitude Long Endurance (HALE) UASs like Predator and Global Hawk, and how those lessons are being applied to sUAS development. This paper will focus on application, rather a deep dive into the technology, and will highlight improving data management through these new technologies.

Sensor Web↗

UASs in the VOG/Edge/FOG Sensor Web Environment

This paper will describe the evolution of information collection, derivation and delivery mechanisms in sensor webs utilizing Uninhabited Aerial Systems (UAS).We will discuss the movement to "Fog Computing", also known as Edge Computing. Fog Computing facilitates the distribution of common operations and networking between edge devices and cloud computing facilities, optimizing the production of actionable intelligence. Initially, UASs utilized onboard data collection as standard, with minimal data downloaded directly. Information products were derived in conventional computational environments, generally desk top computers, and information products made available to the Science Community in weeks or months. With the increased availability, and increasingly lower costs, of beyond line of sight (BLOS) satellite based communication, transmission rates and data volumes increased, and processing migrated to Cloud based services. Contemporary UASs are moving some of that information product derivation to on vehicle services, and are creating a distributed Cloud/Fog environment. The Author will describe the technological advances that have made this possible, including low power multi-core Central Processing Units (CPU), and, more recently, the availability of high end Graphical Processing Units (GPU) that consume only a few watts. Intelligent system software, leveraging these hardware advances, finally allows for information product generation on-board, rather than simple data collection. Additionally, intelligent flight control systems now support mutual vehicle to vehicle collaboration, allowing UASs to create ad-hoc sensor webs on demand, as required. Also discussed will be the lessons learned by the Authors' development of data systems for NASA's large High Altitude Long Endurance (HALE) UASs like Predator and Global Hawk, and how those lessons are being applied to other UAS development This paper will focus on applications, rather a deep dive into the technology, and will highlight improving data management through these new technologies.

UAS↗

A Novel Data-based Stochastic Distribution Control for Non-Gaussian Stochastic Systems

In this note, we present a novel data-based approach to investigate the non-Gaussian stochastic distribution control problem. As the motivation of this note, the existing methods have been summarised regarding to the drawbacks, for example, neural network weights training for unknown stochastic distribution and so on. To overcome these disadvantages, a new transformation for dynamic probability density function is given by kernel density estimation using interpolation. Based upon this transformation, a representative model has been developed while the stochastic distribution control problem has been transformed into an optimisation problem. Then, data-based direct optimisation and identification-based indirect optimisation have been proposed. In addition, the convergences of the presented algorithms are analysed and the effectiveness of these algorithms has been evaluated by numerical examples. In summary, the contributions of this note are as follows: 1) a new data-based probability density function transformation is given; 2) the optimisation algorithms are given based on the presented model; and 3) a new research framework is demonstrated as the potential extensions to the existing stochastic distribution control.

42 ENGINEERING↗

SEEDS Direct Imaging of the RV-Detected Companion to V450 Andromedae, and Characterization of the System

We report the direct imaging detection of a low-mass companion to a young, moderately active star V450 And, that was previously identified with the radial velocity (RV) method. The companion was found in high-contrast images obtained with the Subaru Telescope equipped with the HiCIAO camera and AO188 adaptive optics system. From the public ELODIE and SOPHIE archives we extracted available high-resolution spectra and RV measurements, along with RVs from the Lick planet search program. We combined our multi-epoch astrometry with these archival, partially unpublished RVs, and found that the companion is a low-mass star, not a brown dwarf, as previously suggested. We found the best-fitting dynamical masses to be m(sub 1) = 1.141(sup + 0.037, sub - 0.091) and m(sub 2) = 0.279(sup + 0.023, sub - 0.020) solar mass. We also performed spectral analysis of the SOPHIE spectra with the iSpec code. Hipparcos time-series photometry shows a periodicity of P = 5.743 day, which is also seen in the SOPHIE spectra as an RV modulation of the star A. We interpret it as being caused by spots on the stellar surface, and the star to be rotating with the given period. From the rotation and level of activity, we found that the system is 380(sup + 220, sub -100) Myr old, consistent with an isochrone analysis (220 (sup +2120, sub -90) Myr). This work may serve as a test case for future studies of low mass stars, brown dwarfs, and exoplanets by combination of RV and direct imaging data.

direct imaging detection of a low-mass companion↗

Characterization of actinide abundances and isotopic compositions by HR-ICP-MS

In this report, we present actinide isotopic and elemental data from fallout melt glass using high resolution inductively coupled plasma mass spectrometry (HR-ICP-MS). This is an analytical technique that requires minimal sample preparation. These data are directly compared to the results of high precision isotopic analyses and elemental assay by multi-collector (MC-) ICP-MS, which requires lengthy sample processing involving spiking and purifying aliquots of individual elements. The comparison shows broad overlap between the results of the two techniques. Thus, although the data obtained by HR-ICP-MS is of significantly lower precision, it is a viable method to obtain actinide elemental and isotopic data on a more rapid timeframe than traditional high-precision techniques.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

UAS Integration in the NAS Project: Flight Test 3 Data Analysis of JADEM-Autoresolver Detect and Avoid System

The Unmanned Aircraft Systems Integration in the National Airspace System project, or UAS Integration in the NAS, aims to reduce technical barriers related to safety and operational challenges associated with enabling routine UAS access to the NAS. The UAS Integration in the NAS Project conducted a flight test activity, referred to as Flight Test 3 (FT3), involving several Detect-and-Avoid (DAA) research prototype systems between June 15, 2015 and August 12, 2015 at the Armstrong Flight Research Center (AFRC). This report documents the flight testing and analysis results for the NASA Ames-developed JADEM-Autoresolver DAA system, referred to as 'Autoresolver' herein. Four flight test days (June 17, 18, 22, and July 22) were dedicated to Autoresolver testing. The objectives of this test were as follows: 1. Validate CPA prediction accuracy and detect-and-avoid (DAA, formerly known as self-separation) alerting logic in realistic flight conditions. 2. Validate DAA trajectory model including maneuvers. 3. Evaluate TCAS/DAA interoperability. 4. Inform final Minimum Operating Performance Standards (MOPS). Flight test scenarios were designed to collect data to directly address the objectives 1-3. Objective 4, inform final MOPS, was a general objective applicable to the UAS in the NAS project as a whole, of which flight test is a subset. This report presents analysis results completed in support of the UAS in the NAS project FT3 data review conducted on October 20, 2015. Due to time constraints and, to a lesser extent, TCAS data collection issues, objective 3 was not evaluated in this analysis.

flight test↗

Multidirectional Cosmic Ray Ion Detector for Deep Space CubeSats

Understanding the nature of anisotropy of solar energetic protons (SEPs) and galactic cosmic ray (GCR) fluxes in the interplanetary medium is crucial in characterizing time-dependent radiation exposure in interplanetary space for future exploration missions. NASA Glenn Research Center has proposed a CubeSat-based instrument to study solar and cosmic ray ions in lunar orbit or deep space. The objective of Solar Proton Anisotropy and Galactic cosmic ray High Energy Transport Instrument (SPAGHETI) is to provide multi-directional ion data to further understand anisotropies in SEP and GCR flux. The instrument is to be developed using large area detectors fabricated from high density, high purity silicon carbide (SiC) to measure linear energy transfer (LET) of ions. Stacks of these LET detectors are arranged in a CubeSat at orthogonal directions to provide multidirectional measurements. The low-noise, thermally-stable nature of silicon carbide and its radiation tolerance allows the multidirectional array of detector stacks to be packed in a 6U CubeSat without active cooling. A concept involving additional coincidence/anticoincidence detectors and a high energy Cherenkov detector is possible to further expand ion energy range and sensitivity.

Extraterrestrial Radiation↗

Imp 6 measurements in the distant polar cusp during substorms

High time-resolution data from the magnetic field, plasma, energetic particle, and VLF wave experiments performed aboard Imp 6 in a study of the distant dayside cusp during substorms are described. The cusp was studied when its location was slightly equatorward of its normal location and the geomagnetic dipole was tilted in the appropriate direction. The data support both reconnection and diffusion as methods of particle entry to the magnetosphere. The evidence (1) indicates an acceleration process to explain enhancements of 400 to 600-km/sec protons above their magnetosheath intensities, and (2) suggests convection of field lines over the polar cap as a means of explaining the lack of low-energy protons near the low-latitude boundary of the cusp. Magnetic field fluctuations, a perturbation vector, ion cyclotron waves, and an abrupt change in the intensity of both whistler waves and electrostatic waves are characterized.

Fairfield, D. H.↗

Multiple melanocortin receptors are expressed in bone cells

Melanocortin receptors belong to the seven transmembrane domain, G-protein coupled family of receptors. There are five members of this receptor family labeled MC1R-MC5R. These receptors are activated by fragments derived from a larger molecule, proopiomelanocortin (POMC) and include ACTH, alpha beta and gamma-MSH and beta-endorphin. Because of in vitro and in vivo data suggesting direct effects of these POMC molecules on bone and bone turnover, we examined bone and bone derived cells for the presence of the various members of the melanocortin receptor family. We report that the five known melanocortin receptors are expressed to varying degrees in osteoblast-like and osteoclastic cells. POMC fragments increased proliferation and expression of a variety of genes in osteoblastic cells. Furthermore, POMC mRNA was detected in osteoclastic cells. These data demonstrate that POMC-derived peptide hormones acting through high affinity melanocortin receptors have specific effects on bone cells. Thus, in addition to the indirect effects of POMC-derived hormones on bone turnover through their modulation of steroid hormone secretion, POMC fragments may have direct and specific effects on bone cell subpopulations.

NASA Discipline Musculoskeletal↗

On the cosmic ray diffusion in a violent interstellar medium

A variety of the available observational data on the cosmic ray (CR) spectrum, anisotropy and composition are in good agreement with a suggestion on the diffusion propagation of CR with energy below 10(15) eV in the interstellar medium. The magnitude of the CR diffusion coefficient and its energy dependence are determined by interstellar medium (ISM) magnetic field spectra. Direct observational data on magnetic field spectra are still absent. A theoretical model to the turbulence generation in the multiphase ISM is resented. The model is based on the multiple generation of secondary shocks and concomitant large-scale rarefactions due to supernova shock interactions with interstellar clouds. The distribution function for ISM shocks are derived to include supernova statistics, diffuse cloud distribution, and various shock wave propagation regimes. This permits calculation of the ISM magnetic field fluctuation spectrum and CR diffusion coefficient for the hot phase of ISM.

Bykov, A. M.↗

Doping evolution of the Mott–Hubbard landscape in infinite-layer nickelates

The recent observation of superconductivity in N d 0.8 S r 0.2 N i O 2 has raised fundamental questions about the hierarchy of the underlying electronic structure. Calculations suggest that this system falls in the Mott–Hubbard regime, rather than the charge-transfer configuration of other nickel oxides and the superconducting cuprates. Here, we use state-of-the-art, locally resolved electron energy-loss spectroscopy to directly probe the Mott–Hubbard character of N d 1 − x S r x N i O 2 . Upon doping, we observe emergent hybridization reminiscent of the Zhang–Rice singlet via the oxygen-projected states, modification of the Nd 5d states, and the systematic evolution of Ni 3d hybridization and filling. These experimental data provide direct evidence for the multiband electronic structure of the superconducting infinite-layer nickelates, particularly via the effects of hole doping on not only the oxygen but also nickel and rare-earth bands.

36 MATERIALS SCIENCE↗

Investigating ultrafine aerosol turbulent fluxes during atmospheric new particle formation events

New particle formation (NPF) is an important source of atmospheric aerosols, yet quantitatively predicting its occurrence remains challenging, partly because ground-based measurements cannot capture NPF accurately if they occur in the upper atmosphere. While observations have confirmed the presence of new particles near the top of the planetary boundary layer (PBL), their origins and the direction of their vertical transport have remained ambiguous. Here, we propose and validate an analytical framework using airborne eddy-covariance (EC) and continuous wavelet transform (CWT) to directly quantify the vertical flux of newly formed particles and determine its dominant vertical transportation direction. Analyzing data from a dedicated airborne campaign over the Southern Great Plains, we observed a persistent and strong downward particle flux during NPF events, with a mean value of 133.8 cm?3 m s?¹ downward flux in the entrainment zone, whereas fluxes on non-NPF days were negligible. Our spectral analysis further confirms that these directional fluxes can be reliably captured using standard 1 Hz aerosol instrumentation. These findings suggest that new particle formation, driven by the entrainment of air from the overlying residual/stable layer during PBL growth, is a significant and potentially understudied source of boundary layer aerosols. The framework presented here provides a methodology to correctly attribute NPF events to specific altitudes, thereby improving the mechanistic understanding required for accurate atmospheric models.

Zhang, Ruoyu↗

Proton magnetic relaxation and internal rotations in tetramethylammonium cadmium chloride

Nuclear magnetic resonance (NMR) and relaxation studies of the proton spin-lattice relaxation time (PSLRT) and proton second moment (PSM) are reported. Tetramethylammonium cadmium chloride (TMCC) was selected as a diamagnetic member of the isomorphic series, and hence proton data relate directly to the motion of the tetramethylammonium ion in the absence of paramagnetic ions. In the model adopted, the correlation time for hindered motion of one of the methyl groups differs from that of the other three groups in the low-temperature phase below 104 K. PSLRT and PSM values agree closely with experimental data with this model. Crystallographic phase transitions in TMCC occur at 104 K and 119 K according to the PSLRT measurements. Dipolar interactions between adjacent protons account for the PSLR rates below 104 K.

Tsang, T.↗