An overview of research efforts at NASA in support of the stage separation and ascent aerothermodynamics research program is presented. The objective of this work is to develop a synergistic suite of experimental, com...
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ISBN:
(纸本)9781624100260
An overview of research efforts at NASA in support of the stage separation and ascent aerothermodynamics research program is presented. The objective of this work is to develop a synergistic suite of experimental, computational, and engineering tools and methods to apply to vehicle separation across the transonic to hypersonic speed regimes. Proximity testing of a generic bimese wing-body configuration is on-going in the transonic (Mach numbers 0.6, 1.05, and 1.1), supersonic (Mach numbers 2.3, 3.0, and 4.5) and hypersonic (Mach numbers 6 and 10) speed regimes in four wind tunnel facilities at the NASA Langley Research Center. An overset grid, Navier-Stokes flow solver has been enhanced and demonstrated on a matrix of proximity cases and on a dynamic separation simulation of the bimese configuration. Steady-state predictions with this solver were in excellent agreement with wind tunnel data at Mach 3 as were predictions via a Cartesian-grid Euler solver. Experimental and computational data have been used to evaluate multi-body enhancements to the widely-used Aerodynamic Preliminary analysis System, an engineering methodology, and to develop a new software package, "SepSim," for the simulation and visualization of vehicle motions in a stage separation scenario. Web-based software will be used for archiving information generated from this research program into a database accessible to the user community. Thus, a framework has been established to study stage separation problems using coordinated experimental, computational, and engineering tools.
We present progress toward developing a "clinician friendly" system for analysis of complex biomedical signals that leverages a high-performance computer cluster and open source software.
We present progress toward developing a "clinician friendly" system for analysis of complex biomedical signals that leverages a high-performance computer cluster and open source software.
Algorithm visualization aims to facilitate the understanding of algorithms by using graphics and animation to reify the execution of an algorithm on selected input data. However, many current visualization techniques ...
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Algorithm visualization aims to facilitate the understanding of algorithms by using graphics and animation to reify the execution of an algorithm on selected input data. However, many current visualization techniques suffer from a variety of problems, such as lack of focus, presentation at a single level of abstraction, and concentration on low-level steps rather than on high-level properties such as invariants. In this paper, we present a new approach to learning algorithms that aims to overcome these drawbacks. An algorithm is explained at various levels of abstraction. Each level is designed to present a single operation used in the algorithm. Operations are shown in a textual form of a pseudocode, but there is also an associated visualization.
We discribe how to extract and visually explore the topology of an open, large scale, hypertext system such as the Web? We address this issue by developing an experimental tool for extracting, exploring and analyzing ...
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We discribe how to extract and visually explore the topology of an open, large scale, hypertext system such as the Web? We address this issue by developing an experimental tool for extracting, exploring and analyzing Aggregates of Web documents. This tool, called TARFNTe, includes a crawling technology, and algorithms for both content analysis and authority graphs calculations (as Kleinberg's HITS), linked with visualization solutions. We provide series of experimental results on different topics that allow us to describe the web's structure in terms of topic Aggregates. The TARENTe system was designed to provide multiple services including Web crawling, network analysis, data mining and information visualization tools. For these purposes we chose to build it using an ad hoc modular Java framework, which allows the integration of open-source code for each task. For simplicity concerns we organized the gathering/analyzing information process around a mySQL database, which can be addressed by different crawlers, as well as by multiple infoviz tools and analysis plug-ins.
We develop an algorithm for the learning of the medial axis of temporal random point sets, employing the principal curve analysis. The principal curve analysis is a generalization of principal axis analysis, which is ...
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We develop an algorithm for the learning of the medial axis of temporal random point sets, employing the principal curve analysis. The principal curve analysis is a generalization of principal axis analysis, which is a standard method for dataanalysis in pattern recognition.
Tracers provide users with useful information about program executions. A tracer can be used for many purposes. Embedded in an interactive console, it enables users to investigate program executions. It can also be th...
ISBN:
(纸本)3540226710
Tracers provide users with useful information about program executions. A tracer can be used for many purposes. Embedded in an interactive console, it enables users to investigate program executions. It can also be the front-end of visualization tools, or it can be used by an automatic process to monitor execution behaviors. For each purpose, the requested information is similar but slightly different. It is therefore important to be able to interact with the tracer in order to tune the sent information. We propose a so-called tracer driver. From a single tracer, it provides a powerful front-end for multiple dynamic analysis tools while limiting the overhead of the trace generation. The tracer driver can be used both synchronously and asynchronously. The relevant execution information is specified by flexible event patterns. A large variety of trace data can be given either systematically or on demand. The proposed tracer driver has been designed and experimented in the context of constraint logic programming, within Codeine, a tracer for GNU-Prolog [1], and connected to a set of graphical tools.
The amount of data that must be collected for one to decide on a course of action, nowadays and in any field, is nothing if extraordinary. The three-dimensional graphic representation of data is a powerful tool for it...
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The amount of data that must be collected for one to decide on a course of action, nowadays and in any field, is nothing if extraordinary. The three-dimensional graphic representation of data is a powerful tool for its analysis. And the possibility for interaction and browsing throughout these data makes this analysis much more interesting and productive. Nevertheless, one doesn't usually make a decision alone, and most tools are of a single-user nature, which jeopardizes the decision-making process, especially if those involved are distant from each other, geographically speaking. With a collaborative information visualization environment, it is possible to debate over the same data and change them if necessary, in real time, diminishing time and avoiding mistakes in the decision-making process. Therefore, this paper proposes a Web-based collaborative tool for datavisualization using Java, EAI (external authoring interface) and VRML (Virtual Reality Modeling Language).
Parallel coordinates are widely used in many applications for visualization of multivariate data. Because of the nature of parallel coordinates, the visualization technique is often used for data overview. However, wh...
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Parallel coordinates are widely used in many applications for visualization of multivariate data. Because of the nature of parallel coordinates, the visualization technique is often used for data overview. However, when the number of tuples to be visualized becomes very large, this technique makes it difficult to distinguish the overall structure. In This work we present a novel technique which uses a classification approach, the self-organizing map (an unsupervised learning algorithm), to solve this problem by creating an initial clustering of the data. By initially only visualizing the resulting representational clusters, the inherited global structure can be shown. Using linked views and allowing the user to perform drill-down and filtering on these representations reveals the single data items without loss of context.
The proceedings contain 30 papers. The special focus in this conference is on Grid Computing. The topics include: EU funded grid development in Europe;mapping scientific workflows onto the grid;a low-cost rescheduling...
ISBN:
(纸本)3540228888
The proceedings contain 30 papers. The special focus in this conference is on Grid Computing. The topics include: EU funded grid development in Europe;mapping scientific workflows onto the grid;a low-cost rescheduling policy for dependent tasks on grid computing systems;an advanced architecture for a commercial grid infrastructure;managing MPI applications in grid environments;mpich-g2 implementation of an interactive artificial neural network training;integration of blood flow visualization on the grid;a migration framework for executing parallel programs in the grid;connecting condor pools into computational grids by jini;overview of an architecture enabling grid based application service provision;a grid-enabled adaptive problem solving environment;workflow support for complex grid applications;towards an UML based graphical representation of grid workflow applications;software engineering in the EU crossgrid project;monitoring message-passing parallel applications in the grid with GRM and mercury monitor;using global snapshots to access data streams on the grid;a unified monitoring and performance analysis system for the grid;application monitoring in crossgrid and other grid projects;grid infrastructure monitoring as reliable information service;towards a protocol for the attachment of semantic descriptions to grid services;enabling knowledge discovery services on grids and a grid service framework for metadata management in self-e-learning networks.
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