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At least 415 records · Page 23

UWB Technology and Applications on Space Exploration

Ultra-wideband (UWB), also known as impulse or carrier-free radio technology, is one promising new technology. In February 2002, the Federal Communications Commission (FCC) approved the deployment of this technology. It is increasingly recognized that UWB technology holds great potential to provide significant benefits in many terrestrial and space applications such as precise positioning/tracking and high data rate mobile wireless communications. This talk presents an introduction to UWB technology and some applications on space exploration. UWB is characterized by several uniquely attractive features, such as low impact on other RF systems due to its extremely low power spectral densities, immunity to interference from narrow band RF systems due to its ultra-wide bandwidth, multipath immunity to fading due to ample multipath diversity, capable of precise positioning due to fine time resolution, capable of high data rate multi-channel performance. The related FCC regulations, IEEE standardization efforts and industry activities also will be addressed in this talk. For space applications, some projects currently under development at NASA Johnson Space Center will be introduced. These include the UWB integrated communication and tracking system for Lunar/Mars rover and astronauts, UWB-RFID ISS inventory tracking, and UWB-TDOA close-in high resolution tracking for potential applications on robonaut.

Ngo, Phong↗

Spectral Analysis of the Accretion Flow in NGC 1052 with Suzaku

We present an analysis of the 101 ks, 2007 Suzaku spectrum of the LINER galaxy NGC 1052. The 0:3..10 keV continuum is well-modeled by a power-law continuum modified by Galactic and intrinsic absorption, and exhibits a soft, thermal emission component below 1 keV. Both a narrow core and a broader component of Fe-Ka emission are robustly detected at 6:4 keV. While the narrow line is consistent with an origin in material distant from the black hole, the broad line is best fit empirically by a model that describes fluorescent emission from the inner accretion disk around a rapidly rotating black hole. We find no direct evidence for Comptonized reflection of the hard X-ray source by the disk above 10 keV, however, which casts doubt on the hypothesis that the broad iron line is produced in a standard accretion disk. We explore other possible scenarios for producing this spectral feature and conclude that the high equivalent width and full width half maximum velocity of the broad iron line (v greater than or equals 0:37c) necessitate an origin within d approx. 8r(sub g) of the hard X-ray source. Based on the confirmed presence of a strong radio jet in this source, the broad iron line may be produced in dense plasma at the base of the jet, implying that emission mechanisms in the central-most portions of active galactic nuclei are more complex than previously thought.

Brenneman, L. W.↗

On Small Disturbance Ascent Vent Behavior

As a spacecraft undergoes ascent in a launch vehicle, its ambient pressure environment transitions from one atmosphere to high vacuum in a matter of a few minutes. Venting of internal cavities is necessary to prevent the buildup of pressure differentials across cavity walls. These pressure differentials are often restricted to low levels to prevent violation of container integrity. Such vents usually consist of fixed orifices, ducts, or combinations of both. Duct conductance behavior is fundamentally different from that for orifices in pressure driven flows governing the launch vehicle ascent depressurization environment. Duct conductance is governed by the average pressure across its length, while orifice conductance is dictated by a pressure ratio. Hence, one cannot define a valid equivalent orifice for a given duct across a range of pressure levels. This presentation discusses development of expressions for these two types of vent elements in the limit of small pressure differentials, explores conditions for their validity, and compares their features regarding ascent depressurization performance.

Venting↗

Launch Lock Mechanism for Resource Prospector Rover

The Resource Prospector Rover is being designed to carry the RESOLVE (Regolith Environment Science, and Oxygen Lunar Volatile Extraction) payload on a mission to the Moon to prospect for water ice. This is a joint project between KSC Swamp Works UB-R1 and JSC. JSC is building the Resource Prospector 2015 (RP15) rover and KSC designed and fabricated a Launch-Lock (LL) hold down mechanism for the rover. The LL mechanism will attach and support the rover on a Lunar Lander during launch and transit to the moon, then release the RP15 rover after touchdown on the lunar surface. This report presents the design and development of the LL mechanism and its unique features which make it suitable for this lunar exploration mission. An EDU (engineering development unit) prototype of the LL has been built and tested at KSC which is the subject of this paper.

Lunar Lander↗

Investigation of Carbon Fiber Architecture in Braided Composites Using X-Ray CT Inspection

During the fabrication of braided carbon fiber composite materials, process variations occur which affect the fiber architecture. Quantitative measurements of local and global fiber architecture variations are needed to determine the potential effect of process variations on mechanical properties of the cured composite. Although non-destructive inspection via X-ray CT imaging is a promising approach, difficulties in quantitative analysis of the data arise due to the similar densities of the material constituents. In an effort to gain more quantitative information about features related to fiber architecture, methods have been explored to improve the details that can be captured by X-ray CT imaging. Metal-coated fibers and thin veils are used as inserts to extract detailed information about fiber orientations and inter-ply behavior from X-ray CT images.

braided composites↗

The Gmao Hybrid 4d-Envar Observing System Simulation Experiment Framework.

This work describes the extension of the Global Modeling and Assimilation Office (GMAO) Observing System Simulation Experiment (OSSE) framework to use a hybrid 4D-EnVar scheme instead of 3D-Var. The original 3D-Var and hybrid 4D-EnVar OSSEs use the same version of the data assimilation system (DAS) so that a direct comparison is possible in terms of the validation with respect to their corresponding real cases. Rather than quantifying the differences between the two data assimilation methodologies, a short inter-comparison of upgrading from a 3D- to a 4D-OSSE is provided to highlight aspects where this change matters to the OSSE community and to identify features of data assimilation that can only be explored in a four-dimensional OSSE framework. A short validation of the hybrid 4D-EnVar OSSE shows that conclusions from previous assessments of the 3D-Var OSSE in its ability to mimic the behavior of the real system still hold with the same caveats. Furthermore, some aspects of the ensemble configuration and behavior are discussed along with forecast sensitivity to observation impacts (FSOI). Estimates of error standard deviations are shown to be smaller in the hybrid 4D-EnVar OSSE but with little impact on the character of the error. A discussion on future work directions focuses on exploring the four-dimensional aspect such as the error distribution within the assimilation window or four-dimensional handling of high-temporal density observations.

Data assimilation↗

Interactive Computer Graphics

Aerospace data analysis tools that significantly reduce the time and effort needed to analyze large-scale computational fluid dynamics simulations have emerged this year. The current approach for most postprocessing and visualization work is to explore the 3D flow simulations with one of a dozen or so interactive tools. While effective for analyzing small data sets, this approach becomes extremely time consuming when working with data sets larger than one gigabyte. An active area of research this year has been the development of data mining tools that automatically search through gigabyte data sets and extract the salient features with little or no human intervention. With these so-called feature extraction tools, engineers are spared the tedious task of manually exploring huge amounts of data to find the important flow phenomena. The software tools identify features such as vortex cores, shocks, separation and attachment lines, recirculation bubbles, and boundary layers. Some of these features can be extracted in a few seconds; others take minutes to hours on extremely large data sets. The analysis can be performed off-line in a batch process, either during or following the supercomputer simulations. These computations have to be performed only once, because the feature extraction programs search the entire data set and find every occurrence of the phenomena being sought. Because the important questions about the data are being answered automatically, interactivity is less critical than it is with traditional approaches.

Kenwright, David↗

Superthermal ion signatures of auroral acceleration processes

The occurrence of non-Maxwellian superthermal features in the auroral topside ionosphere distribution functions has been documented by means of the retarding ion mass spectrometer on the Dynamics Explorer 1 spacecraft. Attention is given to a representative sampling of the observed features and their spatial morphology, as observed at altitudes ranging from a few thousand km to a few earth radii. The observations in question reveal a clear distinction between classical polar wind ion outflow and O(+)-enhanced superthermal flows, and confirm the importance of low altitude transverse acceleration in ionospheric plasma transport, as suggested by previous observations.

Moore, T. E.↗

Direct Manipulation in Virtual Reality

Virtual Reality interfaces offer several advantages for scientific visualization such as the ability to perceive three-dimensional data structures in a natural way. The focus of this chapter is direct manipulation, the ability for a user in virtual reality to control objects in the virtual environment in a direct and natural way, much as objects are manipulated in the real world. Direct manipulation provides many advantages for the exploration of complex, multi-dimensional data sets, by allowing the investigator the ability to intuitively explore the data environment. Because direct manipulation is essentially a control interface, it is better suited for the exploration and analysis of a data set than for the publishing or communication of features found in that data set. Thus direct manipulation is most relevant to the analysis of complex data that fills a volume of three-dimensional space, such as a fluid flow data set. Direct manipulation allows the intuitive exploration of that data, which facilitates the discovery of data features that would be difficult to find using more conventional visualization methods. Using a direct manipulation interface in virtual reality, an investigator can, for example, move a data probe about in space, watching the results and getting a sense of how the data varies within its spatial volume.

Bryson, Steve↗

The 67 Hz Feature in the Black Hole Candidate GRS 1915+105 as a Possible Diskoseismic Mode

The Rossi X-Ray Timing Explorer has made feasible for the first time the search for high-frequency (greater than or equal to 100 Hz) periodic features in Black Hole Candidate (BHC) systems. Such a feature, with a 67 Hz frequency, recently has been discovered in the BHC GRS 1915+105 (Morgan, Remillard, & Greiner). This feature is weak (rms variability approx. 0.3%-1.6%), stable in frequency (to within approx. 2 Hz) despite appreciable luminosity fluctuations, and narrow (quality factor Q approx. 20). Several of these properties are what one expects for a 'diskoseismic' g-mode in an accretion disk about a 10.6 M(solar mass) (nonrotating) to 36.3 M(solar mass) (maximally rotating) black hole (if we are observing the fundamental-mode frequency). We explore this possibility by considering the expected luminosity modulation, as well as possible excitation and growth mechanisms-including turbulent excitation, damping, and 'negative' radiation damping. We conclude that a diskoseismic interpretation of the observations is viable.

Nowak, Michael A.↗

Highly Parallel Computing Architectures by using Arrays of Quantum-dot Cellular Automata (QCA): Opportunities, Challenges, and Recent Results

There has been significant improvement in the performance of VLSI devices, in terms of size, power consumption, and speed, in recent years and this trend may also continue for some near future. However, it is a well known fact that there are major obstacles, i.e., physical limitation of feature size reduction and ever increasing cost of foundry, that would prevent the long term continuation of this trend. This has motivated the exploration of some fundamentally new technologies that are not dependent on the conventional feature size approach. Such technologies are expected to enable scaling to continue to the ultimate level, i.e., molecular and atomistic size. Quantum computing, quantum dot-based computing, DNA based computing, biologically inspired computing, etc., are examples of such new technologies. In particular, quantum-dots based computing by using Quantum-dot Cellular Automata (QCA) has recently been intensely investigated as a promising new technology capable of offering significant improvement over conventional VLSI in terms of reduction of feature size (and hence increase in integration level), reduction of power consumption, and increase of switching speed. Quantum dot-based computing and memory in general and QCA specifically, are intriguing to NASA due to their high packing density (10(exp 11) - 10(exp 12) per square cm ) and low power consumption (no transfer of current) and potentially higher radiation tolerant. Under Revolutionary Computing Technology (RTC) Program at the NASA/JPL Center for Integrated Space Microelectronics (CISM), we have been investigating the potential applications of QCA for the space program. To this end, exploiting the intrinsic features of QCA, we have designed novel QCA-based circuits for co-planner (i.e., single layer) and compact implementation of a class of data permutation matrices, a class of interconnection networks, and a bit-serial processor. Building upon these circuits, we have developed novel algorithms and QCA-based architectures for highly parallel and systolic computation of signal/image processing applications, such as FFT and Wavelet and Wlash-Hadamard Transforms.

Fijany, Amir↗

Discovery of Cyclotron Resonance Features in the Soft Gamma Repeater SGR 1806-20

We report evidence for cyclotron resonance features from the Soft Gamma Repeater SCR 1806-20 in outburst, detected with the Rossi X-ray Timing Explorer in the spectrum of a long, complex precursor that preceded a strong burst. The features consist of a narrow 5.0 keV absorption line with modulation near its second and third harmonics (at 11.2 keV and 17.5 keV respectively). The line features are transient and are detected in the harder part of the precursor. The 5.0 keV feature is strong, with an equivalent width of approx. 500 eV, and a narrow width of < 0.4 keV. Interpreting the features as electron cyclotron lines in the context of accretion models leads to a large mass-radius ratio (M/R > 0.3 Solar Mass/km) that is inconsistent with neutron stars, or requires a low (5 - 7) x 10(exp 11) G magnetic field that is unlikely for SGRs. The line widths are also narrow compared to those of electron cyclotron resonances observed so far in X-ray pulsars. In the magnetar picture, the features are plausibly explained as ion cyclotron resonances in an ultra-strong magnetic field, which have recently been predicted from magnetar candidates. In this view, the 5.0 keV feature is consistent with a proton cyclotron fundamental whose energy and width are close to model predictions. The line energy would correspond to a surface magnetic field of 1.0 x 10(exp 15) G for SGR 1806-20, in good agreement with that inferred from the spin-down measure in the source.

Ibrahim, A. I.↗

Discovery of Cyclotron Resonance Features in the Soft Gamma Repeater SGR 1806-20

We report evidence of cyclotron resonance features from the Soft Gamma Repeater SGR 1806-20 in outburst, detected with the Rossi X-ray Timing Explorer in the spectrum of a long, complex precursor that preceded a strong burst. The features consist of a narrow 5.0 keV absorption line with modulation near its second and third harmonics (at 11.2 keV and 17.5 keV respectively). The line features are transient and are detected in the harder part of the precursor. The 5.0 keV feature is strong, with an equivalent width of approx. 500 eV and a narrow width of less than 0.4 keV. Interpreting the features as electron cyclotron lines in the context of accretion models leads to a large mass-radius ratio (M/R greater than 0.3 solar mass/km) that is inconsistent with neutron stars or that requires a low (5-7) x 10(exp 11) G magnetic field that is unlikely for SGRs. The line widths are also narrow compared with those of electron cyclotron resonances observed so far in X-ray pulsars. In the magnetar picture, the features are plausibly explained as ion cyclotron resonances in an ultra-strong magnetic field that have recently been predicted from magnetar candidates. In this view, the 5.0 keV feature is consistent with a proton cyclotron fundamental whose energy and width are close to model predictions. The line energy would correspond to a surface magnetic field of 1.0 x 10(exp 15) G for SGR 1806-20, in good agreement with that inferred from the spin-down measure in the source.

Ibrahim, Alaa I.↗

Properties of Subsurface Soil Cores from Four Geologic Provinces Surrounding Mars Desert Research Station, Utah: Characterizing Analog Martian Soil in a Human Exploration Scenario

The DOMEX program is a NASA-MMAMA funded project featuring simulations of human crews on Mars focused on science activities that involve collecting samples from the subsurface using both manual and robotic equipment methods and analyzing them in the field and post mission. A crew simulating a human mission to Mars performed activities focused on subsurface science for 2 weeks in November 2009 at Mars Desert Research Station near Hanksville, Utah --an important chemical and morphological Mars analog site. Activities performed included 1) survey of the area to identify geologic provinces, 2) obtaining soil and rock samples from each province and characterizing their mineralogy, chemistry, and biology; 3) site selection and reconnaissance for a future drilling mission; 4) deployment and testing of Mars Underground Mole, a percussive robotic soil sampling device; and 5) recording and analyzing how crew time was used to accomplish these tasks. This paper summarizes results from analysis of soil cores

Stoker, C. R.↗

Cooperative Exploration of Rough Martian Terrains with the "Scorpion" Legged Robot as an Adjunct to a Rover.

NASA needs autonomous robotic exploration of difficult (rough and/or steep) scientifically interesting Martian terrains. Concepts involving distributed autonomy for cooperative robotic exploration are key to enabling new scientific objectives in robotic missions. We propose to utilize a legged robot as an adjunct scout to a rover for access to difficult - scientifically interesting - terrains (rocky areas, slopes, cliffs). Our final mission scenario involves the Ames rover platform "K9" and Scorpion acting together to explore a steep cliff, with the Scorpion robot rappelling down using the K9 as an anchor as well as mission planner and executive. Cooperation concepts, including wheeled rappelling robots have been proposed before. Now we propose to test the combined advantages of a wheeled vehicle with a legged scout as well as the advantages of merging of high level planning and execution with biologically inspired, behavior based robotics. We propose to use the 8-legged, multifunctional autonomous robot platform Scorpion that is currently capable of: Walking on different terrains (rocks, sand, grass, ...). Perceiving its environment and modifying its behavioral pattern accordingly. These capabilities would be extended to enable the Scorpion to: communicate and cooperate with a partner robot; climb over rocks, rubble piles, and objects with structural features. This will be done in the context of exploration of rough terrains in the neighborhood of the rover, but inaccessible to it, culminating in the added capability of rappelling down a steep cliff for both vertical and horizontal terrain observation.

Colombano, Silvano P.↗

Real-World Driving Features for Identifying Intelligent Driver Model Parameters

Driver behavior models play a significant role in representing different driving styles and the associated relationships with traffic patterns and vehicle energy consumption in simulation studies. The models often serve as a proxy for baseline human driving when assessing energy-saving strategies that alter vehicle velocity. Such models are especially important in connectivity-enabled energy-saving strategy research because they can easily adapt to changing driving conditions like posted speed limits or change in traffic light state. While numerous driver models exist, parametric driver models provide the flexibility required to represent variability in real-world driving through different combinations of model parameters. These model parameters must be informed by a representative set of parameter values for the driver model to adequately represent a real-world driver. It stands to reason that determining the parameter values from real-world driving data would serve the purpose of representing a real-world driver. Although the published literature is replete with techniques and consequences of using real-world driving data to determine parameter values for parametric driver models, none have explored them in the context of using shorter driving features where the parameter values may change over the course of a single trip for the same driver. In this study we consider the “intelligent driver model” (IDM) as our driver behavior model and use real-world driving data from the Transportation Secure Data Center (TSDC) maintained at the National Renewable Energy Laboratory (NREL). The TSDC includes real-world travel data from across the United States, from which NREL has created a wide range of driving routes consisting of road features such as speed limits, stop locations, and turn locations. The real-world driving data are categorized into different driving regimes and extracted into driving features. The driving features are then used to calibrate the parameter values for the IDM. The distribution of the parameters and the relationships among them are reported. The insights obtained from this study enable judicious usage of IDM or similar parametric driver models to represent baseline human driver behavior in simulations.

27 ARPA - Advanced Research Projects Agency-Energy↗

The influence of physical and algorithmic factors on simulated far-field waveforms and source–time functions of underground explosions using unsupervised machine learning

SUMMARY Characterizing explosion sources and differentiating between earthquake and underground explosions using distributed seismic networks becomes non-trivial when explosions are detonated in cavities or heterogeneous ground material. Moreover, there is little understanding of how changes in subsurface physical properties affect the far-field waveforms we record and use to infer information about the source. Simulations of underground explosions and the resultant ground motions can be a powerful tool to systematically explore how different subsurface properties affect far-field waveform features, but there are added variables that arise from how we choose to model the explosions that can confound interpretation. To assess how both subsurface properties and algorithmic choices affect the seismic wavefield and the estimated source functions, we ran a series of 2-D axisymmetric non-linear numerical explosion experiments and wave propagation simulations that explore a wide array of parameters. We then inverted the synthetic far-field waveform data using a linear inversion scheme to estimate source–time functions (STFs) for each simulation case. We applied principal component analysis (PCA), an unsupervised machine learning method, to both the far-field waveforms and STFs to identify the most important factors that control variance in the waveform data and differences between cases. For the far-field waveforms, the largest variance occurs in the shallower radial receiver channels in the 0–50 Hz frequency band. For the STFs, both peak amplitude and rise times across different frequencies contribute to the variance. We find that the ground equation of state (i.e. lithology and rheology) and the explosion emplacement conditions (i.e. tamped versus cavity) have the greatest effect on the variance of the far-field waveforms and STFs, with the ground yield strength and fracture pressure being secondary factors. Differences in the PCA results between the far-field waveforms and STFs could possibly be due to near-field non-linearities of the source that are not accounted for in the estimation of STFs and could be associated with yield strength, fracture pressure, cavity radius and cavity shape parameters. Other algorithmic parameters are found to be less important and cause less variance in both the far-field waveforms and STFs, meaning algorithmic choices in how we model explosions are less important, which is encouraging for the further use of explosion simulations to study how physical Earth properties affect seismic waveform features and estimated STFs.

58 GEOSCIENCES↗

Assessment of Machine Learning Wall Modeling Approaches for Large Eddy Simulation of Gas Turbine Film Cooling Flows: An a Priori Study

Here, in this work, a priori analysis of machine learning (ML) strategies is carried out with the goal of data-driven wall modeling for large eddy simulation (LES) of gas turbine film cooling flows. High-fidelity flow datasets are extracted from wall-resolved LES (WRLES) of flow over a flat plate interacting with the coolant flow supplied by a single row of 7-7-7 shaped cooling holes inclined at 30 degrees with the flat plate at different blowing ratios (BR). The WRLES are performed using the high-order Nek5000 spectral element computational fluid dynamics (CFD) solver. Light gradient boosting machine (LightGBM) is employed as the ML algorithm for the data-driven wall model. Parametric tests are conducted to systematically assess the influence of a wide range of input flow features (velocity components, velocity gradients, pressure gradients, and fluid properties) on the accuracy of ML wall model with respect to prediction of wall shear stress. In addition, the use of spatial stencil and time delay is also explored within the ML wall modeling framework. It is shown that features associated with gradients of the streamwise and spanwise velocity components have a major impact on the prediction fidelity of wall model, while the effect of gradients of wall-normal velocity component is found to be negligible. Moreover, adding flow feature information from an x-y-z spatial stencil significantly improves the ML model accuracy and generalizability compared to just using local flow features from the matching location. Overall, highest prediction accuracy is achieved when both spatial stencil and time delay features are incorporated within the data-driven wall modeling paradigm.

33 ADVANCED PROPULSION SYSTEMS↗