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At least 487 records · Page 27

History of the numerical aerodynamic simulation program

The Numerical Aerodynamic Simulation (NAS) program has reached a milestone with the completion of the initial operating configuration of the NAS Processing System Network. This achievement is the first major milestone in the continuing effort to provide a state-of-the-art supercomputer facility for the national aerospace community and to serve as a pathfinder for the development and use of future supercomputer systems. The underlying factors that motivated the initiation of the program are first identified and then discussed. These include the emergence and evolution of computational aerodynamics as a powerful new capability in aerodynamics research and development, the computer power required for advances in the discipline, the complementary nature of computation and wind tunnel testing, and the need for the government to play a pathfinding role in the development and use of large-scale scientific computing systems. Finally, the history of the NAS program is traced from its inception in 1975 to the present time.

Peterson, Victor L.↗

NASA/NOAA Electronic Theater: An Hour of Spectacular Visualization

The NASA/NOAA Electronic Theater presents Earth science observations and visualizations from space in a historical perspective. Fly in from outer space to Utah, Logan and the USU Agriculture Station. Compare zooms through the Cosmos to the sites of the 2004 Summer and 2002 Winter Olympic games using 1 m IKONOS "Spy Satellite" data. Contrast the 1972 Apollo 17 "Blue Marble" image of the Earth with the latest US and International global satellite images that allow us to view our Planet from any vantage point. See the latest spectacular images h m NASA/NOAA remote sensing missions like Terra, GOES, TRMM, SeaWiF!3,& Landsat 7, of storms & fires like Hurricanes Charlie & Isabel and the LA/San Diego Fire Storms of 2003. See how High Definition Television (HDTV) is revolutionizing the way we do science communication. Take the pulse of the planet on a daily, annual and 30-year time scale. See daily thunderstorms, the annual greening of the northern hemisphere land masses and oceans, fires in Africa, dust storms in Iraq, and carbon monoxide exhaust from global burning. See visualizations featured on Newsweek, TIME, National Geographic, Popular Science covers & National & International Network TV. Spectacular new global visualizations of the observed and simulated atmosphere & oceans are shown. See the currents and vortexes in the oceans that bring up the nutrients to feed tiny plankton and draw the fish, whales and fishermen. See the how the Ocean blooms in response to El Nino/La Nina climate changes. The E-theater will be presented using the latest High Definition TV and video projection technology on a large screen. See the global city lights, and the great NE US blackout of August 2003 observed by the "night-vision" DMSP satellite.

Hasier, A. F.↗

An analysis of nearfield normal mode amplitude anomalies of the Landers earthquake

The 1992 Landers earthquake (M(sub w) = 7.3) occurred in the middle of the TERRAscope network. Long-period Rayleigh waves recorded at the TERRAscope stations (delta less than or = 3 deg) after traveling around the Earth show large amplitude anomalies, one order of magnitude larger than spherical Earth predictions up to a period of about 600 s. The ground motions over the epicentral region at and after the arrival of R4-5 are in phase at all stations. These observations are inconsistent with the nearly vertical strike slip mechanism of the Landers earthquake. Synthetic seismograms for a rotating, elliptic, and laterally heterogeneous Earth model calculated by the variational method agree well with the observed waveforms. Calculations for various 3D Earth models demonstrate that the amplitudes are very sensitive to the large scale aspherical structure in the crust and the mantle. The anomalies for modes shorter than 300 s period can be explained by lateral heterogeneity shallower than the upper mantle. Rotation of the Earth and lower mantle heterogeneity are required to explain mode amplitudes at longer periods. Current whole mantle seismic tomographic models can fully explain the observed amplitudes longer than 300 s. To assess the effect of the high order lateral heterogeneity in the mantle more precise estimate of the crustal correction is required.

Watada, Shingo↗

A Latency-Tolerant Partitioner for Distributed Computing on the Information Power Grid

NASA's Information Power Grid (IPG) is an infrastructure designed to harness the power of graphically distributed computers, databases, and human expertise, in order to solve large-scale realistic computational problems. This type of a meta-computing environment is necessary to present a unified virtual machine to application developers that hides the intricacies of a highly heterogeneous environment and yet maintains adequate security. In this paper, we present a novel partitioning scheme. called MinEX, that dynamically balances processor workloads while minimizing data movement and runtime communication, for applications that are executed in a parallel distributed fashion on the IPG. We also analyze the conditions that are required for the IPG to be an effective tool for such distributed computations. Our results show that MinEX is a viable load balancer provided the nodes of the IPG are connected by a high-speed asynchronous interconnection network.

Das, Sajal K.↗

Prediction of Stiffness and Fatigue Lives of Polymer Matrix Composite Laminates Using Artificial Neural Networks

Machine learning (ML) models are increasingly being used in many engineering fields due to the advancements in ML algorithms and availability of high-speed computing power. One of the most popular ML class of models is artificial neural networks (ANN). ML is increasingly being used in the design and analysis of composite materials and structures, specifically in the constitutive modeling of composite materials with the focus on greatly accelerating multiscale analyses of composite materials and structures through development of surrogate models. Towards that end, both Python and MATLAB-based neural nets have been developed to predict initial stiffness and fatigue life of an eight-ply symmetric polymer matrix composite laminate. Two types of neural networks, a Multilayer Perceptron (MLP) and a Recurrent Neural Network (RNN), have been developed for both platforms. Results show that the both neural net types can provide an excellent estimate of initial stiffness as well as fatigue life of eight-ply symmetric polymer matrix composite laminate. RNNs are better able to capture the shape of the fatigue curve of a laminate. This tool can be very useful for system level studies to obtain an estimate of desired properties and life of PMC composite laminates. The associated surrogate models could also be used in composite multiscale analyses to replace the actual physics-based calculations at lower scales and thereby significantly increase the computational efficiency of such analyses and thus make multiscale analyses a viable industrial tool for large scale structural problems.

Composite↗

Combinatorial Multidomain Mesoporous Chips and a Method for Fractionation, Stabilization, and Storage of Biomolecules

A new fractionation device shows desirable features for exploratory screening and biomarker discovery. The constituent MSCs may be tailored for desired pore sizes and surface properties and for the sequestration and enrichment of extremely low abundant protein and peptides in desired ranges of the mass/charge spectrum. The MSCs are effective in yielding reproducible extracts from complex biological samples as small as 10 microliter in a time as short as 30 minutes. They are inexpensive to manufacture, and allow for scaled up production to attain the simultaneous processing of a large number of samples. The MSCs are multiplexed, label-free diagnostic tools with the potential of biological recognition moiety modification for enhanced specificity. The MSCs may store, protect and stabilize biological fluids, enabling the simplified and cost-effective collection and transportation of clinical samples. The MSC-based device may serve as a diagnostic tool to complement histopathology, imaging, and other conventional clinical techniques. The MSCs mediated identification of disease-specific protein signatures may help in the selection of personalized therapeutic combinations, in the real-time assessment of therapeutic efficacy and toxicity, and in the rational modulation of therapy based on the changes in the protein networks associated with the prognosis and the drug resistance of the disease.

Ferrari, Mauro↗

Evaluation of externally heated pulsed MPD thruster cathodes

Recent interest in solar electric orbit transfer vehicles (SEOTV's) has prompted a reevaluation of pulsed magnetoplasmadynamic (MPD) thruster systems due to their ease of power scaling and reduced test facility requirements. In this work the use of externally heated cathodes was examined in order to extend the lifetime of these thrusters to the 1000 to 3000 hours required for SEOTV missions. A pulsed MPD thruster test facility was assembled, including a pulse-forming network (PFN), ignitor supply and propellant feed system. Results of cold cathode tests used to validate the facility, PFN, and propellant feed system design are presented, as well as a preliminary evaluation of externally heated impregnated tungsten cathodes. The cold cathode thruster was operated on both argon and nitrogen propellants at peak discharge power levels up to 300 kW. The results confirmed proper operation of the pulsed thruster test facility, and indicated that large amounts of gas were evolved from the BaO-CaO-Al2O3 cathodes during activation. Comparison of the expected space charge limited current with the measured vacuum current when using the heated cathode indicate that either that a large temperature difference existed between the heater and the cathode or that the surface work function was higher than expected.

Myers, Roger M.↗

The Contribution of Soil Moisture Information to Forecast Skill: Two Studies

This talk briefly describes two recent studies on the impact of soil moisture information on hydrological and meteorological prediction. While the studies utilize soil moisture derived from the integration of large-scale land surface models with observations-based meteorological data, the results directly illustrate the potential usefulness of satellite-derived soil moisture information (e.g., from SMOS and SMAP) for applications in prediction. The first study, the GEWEX- and ClIVAR-sponsored GLACE-2 project, quantifies the contribution of realistic soil moisture initialization to skill in subseasonal forecasts of precipitation and air temperature (out to two months). The multi-model study shows that soil moisture information does indeed contribute skill to the forecasts, particularly for air temperature, and particularly when the initial local soil moisture anomaly is large. Furthermore, the skill contributions tend to be larger where the soil moisture initialization is more accurate, as measured by the density of the observational network contributing to the initialization. The second study focuses on streamflow prediction. The relative contributions of snow and soil moisture initialization to skill in streamflow prediction at seasonal lead, in the absence of knowledge of meteorological anomalies during the forecast period, were quantified with several land surface models using uniquely designed numerical experiments and naturalized streamflow data covering mUltiple decades over the western United States. In several basins, accurate soil moisture initialization is found to contribute significant levels of predictive skill. Depending on the date of forecast issue, the contributions can be significant out to leads of six months. Both studies suggest that improvements in soil moisture initialization would lead to increases in predictive skill. The relevance of SMOS and SMAP satellite-based soil moisture information to prediction are discussed in the context of these studies.

Koster, Randal↗

Adaptivity in Agent-Based Routing for Data Networks

Adaptivity, both of the individual agents and of the interaction structure among the agents, seems indispensable for scaling up multi-agent systems (MAS s) in noisy environments. One important consideration in designing adaptive agents is choosing their action spaces to be as amenable as possible to machine learning techniques, especially to reinforcement learning (RL) techniques. One important way to have the interaction structure connecting agents itself be adaptive is to have the intentions and/or actions of the agents be in the input spaces of the other agents, much as in Stackelberg games. We consider both kinds of adaptivity in the design of a MAS to control network packet routing. We demonstrate on the OPNET event-driven network simulator the perhaps surprising fact that simply changing the action space of the agents to be better suited to RL can result in very large improvements in their potential performance: at their best settings, our learning-amenable router agents achieve throughputs up to three and one half times better than that of the standard Bellman-Ford routing algorithm, even when the Bellman-Ford protocol traffic is maintained. We then demonstrate that much of that potential improvement can be realized by having the agents learn their settings when the agent interaction structure is itself adaptive.

Wolpert, David H.↗

Stiffness and Fatigue Life Estimator for Polymer Composite Laminates Using Machine Learning

Machine learning (ML) models are increasingly being used in many engineering fields due to the advancements in ML algorithms and availability of high-speed computing power. One of the most popular ML class of models is artificial neural networks (ANN). ML is increasingly being used in the design and analysis of composite materials and structures, specifically in the constitutive modeling of composite materials with the focus on greatly accelerating multiscale analyses of composite materials and structures through development of surrogate models. Towards that end, Python-based neural nets have been developed to predict initial stiffness and fatigue life of an eight-ply symmetric polymer matrix composite laminate. Two types of neural networks, a Multilayer Perceptron (MLP) and a Recurrent Neural Network (RNN), have been established. Results show that both neural net type algorithms can provide an excellent estimate of initial laminate stiffness as well as fatigue life of eight-ply symmetric polymer matrix composite laminates (PMCs). RNNs are better able to capture the shape of the fatigue curve of a laminate. The resulting tool and GUI can be very useful for system level studies to obtain an estimate of desired properties and life of PMC composite laminates. Further, the associated surrogate models can also be used in composite multiscale analyses to replace the actual physics-based calculations at lower scales and thereby significantly increase the computational efficiency of such analyses and thus make micromechanics-based multiscale analyses a viable industrial tool for large scale structural problems.

multiscale analysis↗

Stiffness and Fatigue Life Estimator for Polymer Composite Laminates Using Machine Learning

Machine learning (ML) models are increasingly being used in many engineering fields due to the advancements in ML algorithms and availability of high-speed computing power. One of the most popular ML class of models is artificial neural networks (ANN). ML is increasingly being used in the design and analysis of composite materials and structures, specifically in the constitutive modeling of composite materials with the focus on greatly accelerating multiscale analyses of composite materials and structures through development of surrogate models. Towards that end, Python-based neural nets have been developed to predict initial stiffness and fatigue life of an eight-ply symmetric polymer matrix composite laminate. Two types of neural networks, a Multilayer Perceptron (MLP) and a Recurrent Neural Network (RNN), have been established. Results show that both neural net type algorithms can provide an excellent estimate of initial laminate stiffness as well as fatigue life of eight-ply symmetric polymer matrix composite laminates (PMCs). RNNs are better able to capture the shape of the fatigue curve of a laminate. The resulting tool and GUI can be very useful for system level studies to obtain an estimate of desired properties and life of PMC composite laminates. Further, the associated surrogate models can also be used in composite multiscale analyses to replace the actual physics-based calculations at lower scales and thereby significantly increase the computational efficiency of such analyses and thus make micromechanics-based multiscale analyses a viable industrial tool for large scale structural problems.

multiscale analysis↗

Infrasonic Detection of a Large Bolide over South Sulawesi, Indonesia on October 8, 2009: Preliminary Results

In the morning hours of October 8, 2009, a bright object entered Earth's atmosphere over South Sulawesi, Indonesia. This bolide disintegrated above the ground, generating stratospheric infrasound returns that were detected by infrasonic stations of the global International Monitoring System (IMS) Network of the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) at distances up to 17 500 km. Here we present instrumental recordings and preliminary results of this extraordinary event. Using the infrasonic period-yield relations, originally derived for atmospheric nuclear detonations, we find the most probable source energy for this bolide to be 70+/-20 kt TNT equivalent explosive yield. A unique aspect of this event is the fact that it was apparently detected by infrasound only. Global events of such magnitude are expected only once per decade and can be utilized to calibrate infrasonic location and propagation tools on a global scale, and to evaluate energy yield formula, and event timing.

Silber, E. A.↗

Basin-Scale Assessment of the Land Surface Water Budget in the National Centers for Environmental Prediction Operational and Research NLDAS-2 Systems

The purpose of this study is to evaluate the components of the land surface water budget in the four land surface models (Noah, SAC-Sacramento Soil Moisture Accounting Model, (VIC) Variable Infiltration Capacity Model, and Mosaic) applied in the newly implemented National Centers for Environmental Prediction (NCEP) operational and research versions of the North American Land Data Assimilation System version 2 (NLDAS-2). This work focuses on monthly and annual components of the water budget over 12 National Weather Service (NWS) River Forecast Centers (RFCs). Monthly gridded FLUX Network (FLUXNET) evapotranspiration (ET) from the Max-Planck Institute (MPI) of Germany, U.S. Geological Survey (USGS) total runoff (Q), changes in total water storage (dS/dt, derived as a residual by utilizing MPI ET and USGS Q in the water balance equation), and Gravity Recovery and Climate Experiment (GRACE) observed total water storage anomaly (TWSA) and change (TWSC) are used as reference data sets. Compared to these ET and Q benchmarks, Mosaic and SAC (Noah and VIC) in the operational NLDAS-2 overestimate (underestimate) mean annual reference ET and underestimate (overestimate) mean annual reference Q. The multimodel ensemble mean (MME) is closer to the mean annual reference ET and Q. An anomaly correlation (AC) analysis shows good AC values for simulated monthly mean Q and dS/dt but significantly smaller AC values for simulated ET. Upgraded versions of the models utilized in the research side of NLDAS-2 yield largely improved performance in the simulation of these mean annual and monthly water component diagnostics. These results demonstrate that the three intertwined efforts of improving (1) the scientific understanding of parameterization of land surface processes, (2) the spatial and temporal extent of systematic validation of land surface processes, and (3) the engineering-oriented aspects such as parameter calibration and optimization are key to substantially improving product quality in various land data assimilation systems.

NLDAS-2↗

Airborne Doppler lidar observations of convective phenomena in Oklahoma

On 30 June 1981, the wind fields around a variety of convective clouds, ranging from large thunderstorm complexes to isolated cumulus congestus, were observed in Oklahoma using an airborne Doppler lidar operated by NASA. By steering the pulsed infrared laser beam alternately along differing horizontal directions, a network of independent radial velocity measurements is obtained, which permits high-resolution synthesis of the full horizontal wind vector field in a swath adjacent to the aircraft flight track. The bright reflections of the laser signal by cloud surfaces permit direct identification of the locus of cloud edges, information which is prerequisite to detailed study of the relationships between the winds inside and outside clouds. The horizontal wind fields derived from the lidar data reveal waves and vortices along the gust front of a storm which eventually produced a gust-front tornado, and cloud-scale convergence patterns around an isolated cumulus congestus. Despite the presence of some questionable data associated with undersampling and delayed recording of certain aircraft motion parameters, most of the lidar results appear consistent with cloud photographs made during the experiment, with surface meteorological data, with aircraft flight-level wind data, and with previous observational and theoretical work.

Mccaul, Eugene W., Jr.↗

DSS 14 64-meter antenna S- and X-band efficiency and system noise temperature calibrations, September 1987

The efficiency and noise temperature characteristics of the DSN 64 m antenna network prior to its upgrading to 70 m configuration are documented. The DSS 14 (Goldstone, California) is the last of the three large antennas to be upgraded, and the test results presented document its performance just prior to its downtime during the end of 1987. Antenna area efficiency was found to be somewhat higher at DSS 14 than at DSS 43 (Australia) and DSS 63 (Spain). The peak X-band efficiency was determined to be 49.8 percent (without atmosphere), compared with 45.4 and 45.1 percent for DSS 43 and DSS 63, respectively. The X-band zenith system noise temperature was found to be 1 to 3 Kelvins higher than at the other two stations, depending on which maser was chosen for the measurements. Ascribing efficiency differences to small-scale antenna surface roughness, DSS 14 may be regarded as having a 1.5 to 1.6 mm rms surface as compared to the other two antennas with 1.7 to 1.8 mm rms surfaces.

Slobin, S. D.↗

Cloud-to-Ground Lightning Characteristics of a Major Tropical Cyclone Tornado Outbreak

It is well known that most tropical cyclones (TCs) that make landfall along the Gulf coast of the United States spawn at least a few tornadoes. Although most landfalling TCs generate fewer than a dozen such tornadoes, a small proportion produce large swarm outbreaks, with as many as 25 or more tornadoes. Usually, these major outbreaks occur in large, intense hurricane-strength TCs, but on 15-17 August 1994 Tropical Storm Beryl spun off 37 tornadoes along its path from the Florida panhandle through the mid-Atlantic states. Some 32 of these tornadoes occurred on 16 August 1994 from eastern Georgia to southern Virginia, with most of these taking place in South Carolina. Beryl's 37 tornadoes moved it into what was at that time fifth place historically in terms of TC tornado productivity. The Beryl outbreak is especially noteworthy in that at least three of the tornadoes achieved peak intensity of F3 on the Fujita damage intensity scale. Although no fatalities resulted from the Beryl outbreak, at least 50 persons suffered injuries, and property damages totalled more than $50 million . The Beryl outbreak is a good example of a TC whose greatest danger to the public is its post-landfall severe weather. In this respect, and in the character of its swarm outbreak of tornadoes, it resembles another large tornado outbreak spawned by a relatively weak TC, Hurricane Danny of 1985). In the Danny outbreak, numerous shallow mini-supercell storms were found to have occurred, and it was noted that, because of the storms' relatively shallow depth, cloud-to-ground (CG) lightning was negligible. Better observations of future TC tornado outbreaks, especially with modern surveillance tools such as Doppler radars and the National Lightning Detection Network (NLDN), were recommended. Although the Beryl tornado outbreak is not the first set of TC-spawned tornado storms to be observed with the NLDN, it is one of the largest and likely the most intense such outbreak. The purpose of this paper is to document the NLDN-derived CG lightning characteristics of Beryl's tornadic storms, and to see how they compare with observations of CG lightning activity in other types of severe storms. In particular, we attempt to quantify the CG flash rates of TC tornadic cells, and to discover if there are any characteristics of their CG activity that may be useful to operational forecasters seeking to distinguish which cells are most likely to produce severe weather.

McCaul, Eugene W., Jr.↗

Scientific Objectives, Measurement Needs, and Challenges Motivating the PARAGON Aerosol Initiative

Aerosols are involved in a complex set of processes that operate across many spatial and temporal scales. Understanding these processes, and ensuring their accurate representation in models of transport, radiation transfer, and climate, requires knowledge of aerosol physical, chemical, and optical properties and the distributions of these properties in space and time. To derive aerosol climate forcing, aerosol optical and microphysical properties and their spatial and temporal distributions, and aerosol interactions with clouds, need to be understood. Such data are also required in conjunction with size-resolved chemical composition in order to evaluate chemical transport models and to distinguish natural and anthropogenic forcing. Other basic parameters needed for modeling the radiative influences of aerosols are surface reflectivity and three-dimensional cloud fields. This large suite of parameters mandates an integrated observing and modeling system of commensurate scope. The Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) concept, designed to meet this requirement, is motivated by the need to understand climate system sensitivity to changes in atmospheric constituents, to reduce climate model uncertainties, and to analyze diverse collections of data pertaining to aerosols. This paper highlights several challenges resulting from the complexity of the problem. Approaches for dealing with them are offered in the set of companion papers.

optical depth↗

MDO and Cross-Disciplinary Practice in R&D: A Portrait of Principles and Current Practice

For several decades, Multidisciplinary Design Optimization (MDO) has served an important role in aerospace engineering by incorporating physics based disciplinary models into integrated system or sub-system models for use in research, development, (R&D) and design. This paper examines MDO's role in facilitating the integration of the researchers from different single disciplines during R&D and early design of large-scale complex engineered systems (LaCES) such as aerospace systems. The findings in this paper are summarized from a larger study on interdisciplinary practices and perspectives that included considerable empirical data from surveys, interviews, and ethnography. The synthesized findings were derived by integrating the data with theories from organization science and engineering. The over-arching finding is that issues related to cognition, organization, and social interrelations mostly dominate interactions across disciplines. Engineering issues, such as the integration of hardware or physics-based models, are not as significant. Correspondingly, the data showed that MDO is not the primary integrator of researchers working across disciplines during R&D and early design of LaCES. Cognitive focus such as analysis versus design, organizational challenges such as incentives, and social opportunities such as personal networks often drove the human interactive practices among researchers from different disciplines. Facilitation of the inherent confusion, argument, and learning in crossdisciplinary research was identified as one of several needed elements of enabling successful research across disciplines.

Rivas McGowan, Anna-Maria↗