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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 289 records · Page 16

A Pair of Trans-Golgi Network/Early Endosome-Localized Proteins Facilitate Cytoskeletal-Mediated Root Skewing in Arabidopsis Thaliana

Roots treated with the actin-disrupting compound Latrunculin B (LatB) show stronger gravitropic responses on Earth and dampened straightening responses on a 2-D clinostat. In related experiments using the Biological Research in Canisters (BRIC) hardware, it was found that knockouts to vegetative actin isoforms in Arabidopsis thaliana had more robust root skewing in microgravity and waved more strongly than wild type on hard agar surfaces. These results indicate that the actin cytoskeleton mediates directional root growth in space and on the ground. To gain new insights into the role of actin in directional root growth, we identified mutants that showed differential growth responses to low doses of LatB. In-depth studies of one mutant led to the identification of a trans-Golgi Network (TGN)/Early Endosome (EE)- localized protein that associates with actin. This protein called hypersensitive to LatB 1 (HLB1) colocalized with the ADP-ribosylation-factor guanine nucleotide exchange factor, MIN7/BEN1 (HOPM INTERACTOR7/BREFELDIN A-VISUALIZED ENDOCYTIC TRAFFICKING DEFECTIVE1), at the TGN/EE. HLB1 and MIN7/BEN1 were found to regulate exocytosis and endocytosis, respectively, suggesting that both proteins are involved in actin-mediated membrane traffic. Microtubules, another component of the cytoskeleton, is known to be involved in root skewing. Both hlb1 and min7/ben1 mutants exhibited dampened root skewing on the microtubule stabilizing compound taxol. Taken together, our results support the conclusion that cytoskeletal-membrane interactions contribute to directional root skewing in A. thaliana and is facilitated in part by the TGN/EE-localized HLB1 and MIN7/BEN1 proteins.

Plant Space Biology↗

Instrumentation and data acquisition systems

A comprehensive and integrated measurement system was identified and a design and development effort initiated to meet the criteria imposed by the National Transonic Facility operating environment. Specific measurement areas receiving concentrated attention include: data acquisition, force measurement, pressure instrumentation, flow visualization techniques, model attitude and model deformation measurement, and temperature measurement. The NTF instrument complex will be centered around four 32-bit, 1-microsecond-cycle-time central processing units connected in a multipoint-distributed network configuration. The principal activities to be supported by these computers are: (1) data base management and processing; (2) research measurement data acquisition and display; (3) tunnel and model control; and (4) process monitoring and communication control. The distributed network approach was chosen to modularize the functional software into definable and implementable parts by the various groups involved in the design and to permit use of similar hardware configurations to improve reliability and maintainability.

Guarino, J. F.↗

Wake Vortex Advisory System (WakeVAS) Evaluation of Impacts on the National Airspace System

This report is one of a series that describes an ongoing effort in high-fidelity modeling/simulation, evaluation and analysis of the benefits and performance metrics of the Wake Vortex Advisory System (WakeVAS) Concept of Operations being developed as part of the Virtual Airspace Modeling and Simulation (VAMS) project. A previous study, determined the overall increases in runway arrival rates that could be achieved at 12 selected airports due to WakeVAS reduced aircraft spacing under Instrument Meteorological Conditions. This study builds on the previous work to evaluate the NAS wide impacts of equipping various numbers of airports with WakeVAS. A queuing network model of the National Airspace System, built by the Logistics Management Institute, Mclean, VA, for NASA (LMINET) was used to estimate the reduction in delay that could be achieved by using WakeVAS under non-visual meteorological conditions for the projected air traffic demand in 2010. The results from LMINET were used to estimate the total annual delay reduction that could be achieved and from this, an estimate of the air carrier variable operating cost saving was made.

Smith, Jeremy C.↗

Improving Situational Awareness for First Responders via Mobile Computing

This project looks to improve first responder situational awareness using tools and techniques of mobile computing. The prototype system combines wireless communication, real-time location determination, digital imaging, and three-dimensional graphics. Responder locations are tracked in an outdoor environment via GPS and uploaded to a central server via GPRS or an 802.11 network. Responders can also wirelessly share digital images and text reports, both with other responders and with the incident commander. A pre-built three dimensional graphics model of a particular emergency scene is used to visualize responder and report locations. Responders have a choice of information end points, ranging from programmable cellular phones to tablet computers. The system also employs location-aware computing to make responders aware of particular hazards as they approach them. The prototype was developed in conjunction with the NASA Ames Disaster Assistance and Rescue Team and has undergone field testing during responder exercise at NASA Ames.

Betts, Bradley J.↗

International Space Station Future Correlation Analysis Improvements

Ongoing modal analyses and model correlation are performed on different configurations of the International Space Station (ISS). These analyses utilize on-orbit dynamic measurements collected using four main ISS instrumentation systems: External Wireless Instrumentation System (EWIS), Internal Wireless Instrumentation System (IWIS), Space Acceleration Measurement System (SAMS), and Structural Dynamic Measurement System (SDMS). Remote Sensor Units (RSUs) are network relay stations that acquire flight data from sensors. Measured data is stored in the Remote Sensor Unit (RSU) until it receives a command to download data via RF to the Network Control Unit (NCU). Since each RSU has its own clock, it is necessary to synchronize measurements before analysis. Imprecise synchronization impacts analysis results. A study was performed to evaluate three different synchronization techniques: (i) measurements visually aligned to analytical time-response data using model comparison, (ii) Frequency Domain Decomposition (FDD), and (iii) lag from cross-correlation to align measurements. This paper presents the results of this study.

time synchronization↗

Lyapunov exponents from CHUA's circuit time series using artificial neural networks

In this paper we present the general problem of identifying if a nonlinear dynamic system has a chaotic behavior. If the answer is positive the system will be sensitive to small perturbations in the initial conditions which will imply that there is a chaotic attractor in its state space. A particular problem would be that of identifying a chaotic oscillator. We present an example of three well known different chaotic oscillators where we have knowledge of the equations that govern the dynamical systems and from there we can obtain the corresponding time series. In a similar example we assume that we only know the time series and, finally, in another example we have to take measurements in the Chua's circuit to obtain sample points of the time series. With the knowledge about the time series the phase plane portraits are plotted and from them, by visual inspection, it is concluded whether or not the system is chaotic. This method has the problem of uncertainty and subjectivity and for that reason a different approach is needed. A quantitative approach is the computation of the Lyapunov exponents. We describe several methods for obtaining them and apply a little known method of artificial neural networks to the different examples mentioned above. We end the paper discussing the importance of the Lyapunov exponents in the interpretation of the dynamic behavior of biological neurons and biological neural networks.

Gonzalez, J. Jesus↗

Distributed and collaborative synthetic environments

Fast graphics workstations and increased computing power, together with improved interface technologies, have created new and diverse possibilities for developing and interacting with synthetic environments. A synthetic environment system is generally characterized by input/output devices that constitute the interface between the human senses and the synthetic environment generated by the computer; and a computation system running a real-time simulation of the environment. A basic need of a synthetic environment system is that of giving the user a plausible reproduction of the visual aspect of the objects with which he is interacting. The goal of our Shastra research project is to provide a substrate of geometric data structures and algorithms which allow the distributed construction and modification of the environment, efficient querying of objects attributes, collaborative interaction with the environment, fast computation of collision detection and visibility information for efficient dynamic simulation and real-time scene display. In particular, we address the following issues: (1) A geometric framework for modeling and visualizing synthetic environments and interacting with them. We highlight the functions required for the geometric engine of a synthetic environment system. (2) A distribution and collaboration substrate that supports construction, modification, and interaction with synthetic environments on networked desktop machines.

Bajaj, Chandrajit L.↗

Regional Comparison and Assimilation of GOCART and MODIS Aerosol Optical Depth across the Eastern U.S.

This study compares aerosol optical depths (AOD) products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model and their integrated products with ground measurements across the eastern U.S. from March 1, 2000 to December 31, 2001. The Terra MODIS Level-3 (collection 4) AOD at 0.55 pm has better correlation, but consistently overestimates the values of the Aerosol Robotic Network (AERONET) measurements. GOCART has small biases for a 22-month integration, and slight positive biases are appeared for the cold season. These results are also supported by the comparison with the IMPROVE (Interagency Monitoring of Protected Visual Environments) light extinction index. The optimal interpolation improves the daily-scale RMSE from either MODIS or GOCART alone. However, the regional biases in the aerosol products constitute a major constraint to the optimal estimate of AOD.

Matsui, Toshihisa↗

Dynamic Server-Based KML Code Generator Method for Level-of-Detail Traversal of Geospatial Data

Web-based geospatial client applications such as Google Earth and NASA World Wind must listen to data requests, access appropriate stored data, and compile a data response to the requesting client application. This process occurs repeatedly to support multiple client requests and application instances. Newer Web-based geospatial clients also provide user-interactive functionality that is dependent on fast and efficient server responses. With massively large datasets, server-client interaction can become severely impeded because the server must determine the best way to assemble data to meet the client applications request. In client applications such as Google Earth, the user interactively wanders through the data using visually guided panning and zooming actions. With these actions, the client application is continually issuing data requests to the server without knowledge of the server s data structure or extraction/assembly paradigm. A method for efficiently controlling the networked access of a Web-based geospatial browser to server-based datasets in particular, massively sized datasets has been developed. The method specifically uses the Keyhole Markup Language (KML), an Open Geospatial Consortium (OGS) standard used by Google Earth and other KML-compliant geospatial client applications. The innovation is based on establishing a dynamic cascading KML strategy that is initiated by a KML launch file provided by a data server host to a Google Earth or similar KMLcompliant geospatial client application user. Upon execution, the launch KML code issues a request for image data covering an initial geographic region. The server responds with the requested data along with subsequent dynamically generated KML code that directs the client application to make follow-on requests for higher level of detail (LOD) imagery to replace the initial imagery as the user navigates into the dataset. The approach provides an efficient data traversal path and mechanism that can be flexibly established for any dataset regardless of size or other characteristics. The method yields significant improvements in userinteractive geospatial client and data server interaction and associated network bandwidth requirements. The innovation uses a C- or PHP-code-like grammar that provides a high degree of processing flexibility. A set of language lexer and parser elements is provided that offers a complete language grammar for writing and executing language directives. A script is wrapped and passed to the geospatial data server by a client application as a component of a standard KML-compliant statement. The approach provides an efficient means for a geospatial client application to request server preprocessing of data prior to client delivery. Data is structured in a quadtree format. As the user zooms into the dataset, geographic regions are subdivided into four child regions. Conversely, as the user zooms out, four child regions collapse into a single, lower-LOD region. The approach provides an efficient data traversal path and mechanism that can be flexibly established for any dataset regardless of size or other characteristics.

Baxes, Gregory↗

Data handling and visualization for NASA's science programs

Advanced information systems capabilities are essential to conducting NASA's scientific research mission. Access to these capabilities is no longer a luxury for a select few within the science community, but rather an absolute necessity for carrying out scientific investigations. The dependence on high performance computing and networking, as well as ready and expedient access to science data, metadata, and analysis tools is the fundamental underpinning for the entire research endeavor. At the same time, advances in the whole range of information technologies continues on an almost explosive growth path, reaching beyond the research community to affect the population as a whole. Capitalizing on and exploiting these advances are critical to the continued success of space science investigations. NASA must remain abreast of developments in the field and strike an appropriate balance between being a smart buyer and a direct investor in the technology which serves its unique requirements. Another key theme deals with the need for the space and computer science communities to collaborate as partners to more fully realize the potential of information technology in the space science research environment.

Bredekamp, Joseph H.↗

TOAD Editor

Transferable Output ASCII Data (TOAD) computer program (LAR-13755), implements format designed to facilitate transfer of data across communication networks and dissimilar host computer systems. Any data file conforming to TOAD format standard called TOAD file. TOAD Editor is interactive software tool for manipulating contents of TOAD files. Commonly used to extract filtered subsets of data for visualization of results of computation. Also offers such user-oriented features as on-line help, clear English error messages, startup file, macroinstructions defined by user, command history, user variables, UNDO features, and full complement of mathematical statistical, and conversion functions. Companion program, TOAD Gateway (LAR-14484), converts data files from variety of other file formats to that of TOAD. TOAD Editor written in FORTRAN 77.

Bingle, Bradford D.↗

Image Analysis via Fuzzy-Reasoning Approach: Prototype Applications at NASA

A set of imaging techniques based on Fuzzy Reasoning (FR) approach was built for NASA at Kennedy Space Center (KSC) to perform complex real-time visual-related safety prototype tasks, such as detection and tracking of moving Foreign Objects Debris (FOD) during the NASA Space Shuttle liftoff and visual anomaly detection on slidewires used in the emergency egress system for Space Shuttle at the launch pad. The system has also proved its prospective in enhancing X-ray images used to screen hard-covered items leading to a better visualization. The system capability was used as well during the imaging analysis of the Space Shuttle Columbia accident. These FR-based imaging techniques include novel proprietary adaptive image segmentation, image edge extraction, and image enhancement. Probabilistic Neural Network (PNN) scheme available from NeuroShell(TM) Classifier and optimized via Genetic Algorithm (GA) was also used along with this set of novel imaging techniques to add powerful learning and image classification capabilities. Prototype applications built using these techniques have received NASA Space Awards, including a Board Action Award, and are currently being filed for patents by NASA; they are being offered for commercialization through the Research Triangle Institute (RTI), an internationally recognized corporation in scientific research and technology development. Companies from different fields, including security, medical, text digitalization, and aerospace, are currently in the process of licensing these technologies from NASA.

Dominguez, Jesus A.↗

Measurement of the Dielectric Constant of Seawater at L-Band: Techniques and Measurements

Satellite instruments, that will monitor salinity from space in the near future, require an accurate relationship between salinity/temperature and seawater dielectric constant. This paper will review measurements that were made of the dielectric constant of seawater during the past several years. The objective of the measurements is to determine the dependence of the dielectric constant of seawater on salinity and on temperature, more accurately than in the past. by taking advantage of modem instrumentation. The measurements of seawater permittivity have been performed as a function of salinity and temperature using a transmission resonant cavity technique. The measurements have been made in the salinity range of 10 to 38 psu and in the temperature range of IOU C to 35 C. These results will be useful in algorithm development for sensor systems such as SMOS and Aquarius. The measurement system consists of a brass microwave cavity that is resonant at 1.413 GHz. The seawater is introduced into the cavity through a capillary glass tube having an inner diameter of 0.1 mm. The diameter of the tube has been made very small so that the amount of seawater introduced in the cavity is small - thus maintaining the sensitivity of the measurements and allowing the use of perturbation theory predicting the seawater permittivity. The change in resonant frequency and the change in cavity Q can be used to determine the real and imaginary pare of the dielectric constant of seawater introduced into the slender tube. The microwave measurements are made by an HPS722D network analyzer. The cavity has been immersed in a u~ateriethylene-glycol bath which is connected to a Lauda circulator. The circulator keeps the brass cavity at a temperature constant to within 0.01 degrees. The system is automated using a Visual Basic program to control the analyzer and to collect the data. The results of the dielectric constant measurements of seawater will be presented. The measurement results will be compared with permittivity values generated from the Kline and Swift relationship. Two methods of calibration will be discussed, The errors that each technique introduces into the measurement resulls will be reviewed. Temperature stability, frequency drift and the effect of increasing cavity transmission loss on the unloaded cavity Q will also be discussed.

Lang, R.↗

Usage of Data-Encoded Web Maps with Client Side Color Rendering for Combined Data Access, Visualization and Modeling Purposes

Current approaches to satellite observation data storage and distribution implement separate visualization and data access methodologies which often leads to the need in time consuming data ordering and coding for applications requiring both visual representation as well as data handling and modeling capabilities. We describe an approach we implemented for a data-encoded web map service based on storing numerical data within server map tiles and subsequent client side data manipulation and map color rendering. The approach relies on storing data using the lossless compression Portable Network Graphics (PNG) image data format which is natively supported by web-browsers allowing on-the-fly browser rendering and modification of the map tiles. The method is easy to implement using existing software libraries and has the advantage of easy client side map color modifications, as well as spatial subsetting with physical parameter range filtering. This method is demonstrated for the ASTER-GDEM elevation model and selected MODIS data products and represents an alternative to the currently used storage and data access methods. One additional benefit includes providing multiple levels of averaging due to the need in generating map tiles at varying resolutions for various map magnification levels. We suggest that such merged data and mapping approach may be a viable alternative to existing static storage and data access methods for a wide array of combined simulation, data access and visualization purposes.

Pliutau, Denis↗

Detection of regional air pollution episodes utilizing satellite data in the visual range

A comparative analysis of satellite-observed haze patterns and ground-based aerosol measurements is carried out for July 20-23, 1978. During this period, a significant regional air pollution episode existed across the northeastern United States, accompanied by widespread haze, reduced surface visibility, and elevated sulfate levels measured by the Sulfate Regional Experiment (SURE) network. The results show that the satellite-observed haze patterns correlate closely with the area of reported low surface visibility (less than 4 mi) and high sulfate levels. Quantitative information on total aerosol loading derived from the satellite-digitized data, using an atmospheric radiative transfer model, agrees well with the results obtained from the ground-based measurements.

Bowley, C. J.↗

Sensor fusion IV: Control paradigms and data structures; Proceedings of the Meeting, Boston, MA, Nov. 12-15, 1991

Various papers on control paradigms and data structures in sensor fusion are presented. The general topics addressed include: decision models and computational methods, sensor modeling and data representation, active sensing strategies, geometric planning and visualization, task-driven sensing, motion analysis, models motivated biology and psychology, decentralized detection and distributed decision, data fusion architectures, robust estimation of shapes and features, application and implementation. Some of the individual subjects considered are: the Firefly experiment on neural networks for distributed sensor data fusion, manifold traversing as a model for learning control of autonomous robots, choice of coordinate systems for multiple sensor fusion, continuous motion using task-directed stereo vision, interactive and cooperative sensing and control for advanced teleoperation, knowledge-based imaging for terrain analysis, physical and digital simulations for IVA robotics.

Schenker, Paul S.↗

Emissions Prediction and Measurement for Liquid-Fueled TVC Combustor with and without Water Injection

An investigation is performed to evaluate the performance of a computational fluid dynamics (CFD) tool for the prediction of the reacting flow in a liquid-fueled combustor that uses water injection for control of pollutant emissions. The experiment consists of a multisector, liquid-fueled combustor rig operated at different inlet pressures and temperatures, and over a range of fuel/air and water/fuel ratios. Fuel can be injected directly into the main combustion airstream and into the cavities. Test rig performance is characterized by combustor exit quantities such as temperature and emissions measurements using rakes and overall pressure drop from upstream plenum to combustor exit. Visualization of the flame is performed using gray scale and color still photographs and high-frame-rate videos. CFD simulations are performed utilizing a methodology that includes computer-aided design (CAD) solid modeling of the geometry, parallel processing over networked computers, and graphical and quantitative post-processing. Physical models include liquid fuel droplet dynamics and evaporation, with combustion modeled using a hybrid finite-rate chemistry model developed for Jet-A fuel. CFD and experimental results are compared for cases with cavity-only fueling, while numerical studies of cavity and main fueling was also performed. Predicted and measured trends in combustor exit temperature, CO and NOx are in general agreement at the different water/fuel loading rates, although quantitative differences exist between the predictions and measurements.

Brankovic, A.↗

An Advanced Open-Source Platform for Air Quality Analysis, Visualization, and Prediction

Ambient air pollution is the largest environmental health risk factor, leading to several million premature deaths globally per year. The challenge of combating poor air quality is exacerbated by growing urban populations, changing emissions, and a warming climate. While there have been many advances monitoring and modeling of atmospheric composition, reflected in the dramatic increase in archived Earth Observations, there is no single measurement or method that alone can provide an accurate depiction of the entire atmosphere. The rapidly growing collections of observational and modeling data require us to be smarter about what data to include, and how such data is used. In recent years, NASA has invested significantly in advancing the concepts for Analytics Collaborative Framework (ACF) [5] and New Observing Strategies (NOS) [4] to tackle our software infrastructure need for harmonized data management and dynamic acquisition of diverse measurements for on-demand, interactive, multivariate analysis, and access [3]. It is not enough to have a big data, standalone analytics solution; it is critical that we start integrating data from remote sensing, modeling, and in-situ networks in a harmonized manner that enables timely and data-driven decision-making for air quality management. This work presents the design and development of an Air Quality Analytics Collaborative Framework (AQ ACF), as part of NASA’s Advanced Information Systems Technology (AIST) effort, to establish a data, machine-learning, and numerically driven platform for air quality analysis, visualization, and prediction.

Liu, Qian↗