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NASA NTRS1986

A distributable APSE

A distributed Ada program library is a key element in a distributed Ada Program Support Environment (APSE). To implement this successfully, the program library universe as defined by the Ada Reference Manual must be broken up into independently manageable pieces. This in turn requires the support of a distributed database system, as well as a mechanism for identifying compilation units, linkable subprograms, and Ada types in a decentralized way, to avoid falling victim to the bottlenecks of a global database and/or global unique-identifier manager. It was found that the ability to decentralize Ada program library activity is a major advantage in the management of large Ada programs. Currently, there are 18 resource-catalog revision sets, each in its own Host Interface (HIF) partition, plus 18 partitions for testing each of these, plus 11 partitions for the top-level compiler/linker/program library manager components. Compiling and other development work can proceed in parallel in each of these partitions, without suffering the performance bottlenecks of global locks or global unique-identifier generation.

Taft, Tucker, S.↗

NASA NTRS1987

Automation of Shuttle Tile Inspection - Engineering methodology for Space Station

The Space Systems Integration and Operations Research Applications (SIORA) Program was initiated in late 1986 as a cooperative applications research effort between Stanford University, NASA Kennedy Space Center, and Lockheed Space Operations Company. One of the major initial SIORA tasks was the application of automation and robotics technology to all aspects of the Shuttle tile processing and inspection system. This effort has adopted a systems engineering approach consisting of an integrated set of rapid prototyping testbeds in which a government/university/industry team of users, technologists, and engineers test and evaluate new concepts and technologies within the operational world of Shuttle. These integrated testbeds include speech recognition and synthesis, laser imaging inspection systems, distributed Ada programming environments, distributed relational database architectures, distributed computer network architectures, multimedia workbenches, and human factors considerations.

Wiskerchen, M. J.↗

NASA NTRS1992

Software architecture for a distributed real-time system in Ada, with application to telerobotics

The architecture structure and software design methodology presented is described in the context of telerobotic application in Ada, specifically the Engineering Test Bed (ETB), which was developed to support the Flight Telerobotic Servicer (FTS) Program at GSFC. However, the nature of the architecture is such that it has applications to any multiprocessor distributed real-time system. The ETB architecture, which is a derivation of the NASA/NBS Standard Reference Model (NASREM), defines a hierarchy for representing a telerobot system. Within this hierarchy, a module is a logical entity consisting of the software associated with a set of related hardware components in the robot system. A module is comprised of submodules, which are cyclically executing processes that each perform a specific set of functions. The submodules in a module can run on separate processors. The submodules in the system communicate via command/status (C/S) interface channels, which are used to send commands down and relay status back up the system hierarchy. Submodules also communicate via setpoint data links, which are used to transfer control data from one submodule to another. A submodule invokes submodule algorithms (SMA's) to perform algorithmic operations. Data that describe or models a physical component of the system are stored as objects in the World Model (WM). The WM is a system-wide distributed database that is accessible to submodules in all modules of the system for creating, reading, and writing objects.

Olsen, Douglas R.↗

NASA NTRS1994

Automatic cataloguing and characterization of Earth science data using SE-trees

In the future, NASA's Earth Observing System (EOS) platforms will produce enormous amounts of remote sensing image data that will be stored in the EOS Data Information System. For the past several years, the Intelligent Data Management group at Goddard's Information Science and Technology Office has been researching techniques for automatically cataloguing and characterizing image data (ADCC) from EOS into a distributed database. At the core of the approach, scientists will be able to retrieve data based upon the contents of the imagery. The ability to automatically classify imagery is key to the success of contents-based search. We report results from experiments applying a novel machine learning framework, based on Set-Enumeration (SE) trees, to the ADCC domain. We experiment with two images: one taken from the Blackhills region in South Dakota; and the other from the Washington DC area. In a classical machine learning experimentation approach, an image's pixels are randomly partitioned into training (i.e. including ground truth or survey data) and testing sets. The prediction model is built using the pixels in the training set, and its performance is estimated using the testing set. With the first Blackhills image, we perform various experiments achieving an accuracy level of 83.2 percent, compared to 72.7 percent using a Back Propagation Neural Network (BPNN) and 65.3 percent using a Gaussain Maximum Likelihood Classifier (GMLC). However, with the Washington DC image, we were only able to achieve 71.4 percent, compared with 67.7 percent reported for the BPNN model and 62.3 percent for the GMLC.

Rymon, Ron↗

NASA NTRS1995

Mississippi State University Center for Air Sea Technology FY95 Research Program

The Mississippi State University (MSU) Center for Air Sea Technology (CAST) evolved from the Institute for Naval Oceanography's (INO) Experimental Center for Mesoscale Ocean Prediction (ECMOP) which was started in 1989. MSU CAST subsequently began operation on 1 October 1992 under an Office of Naval Research (ONR) two-year grant which ended on 30 September 1994. In FY95 MSU CAST was successful in obtaining five additional research grants from ONR, as well as several other research contracts from the Naval Oceanographic Office via NASA, the Naval Research Laboratory, the Army Corps of Engineers, and private industry. In the past, MSU CAST technical research and development has produced tools, systems, techniques, and procedures that improve efficiency and overcome deficiency for both the operational and research communities residing with the Department of Defense, private industry, and university ocean modeling community. We continued this effort with the following thrust areas: to develop advanced methodologies and tools for model evaluation, validation and visualization, both oceanographic and atmospheric; to develop a system-level capability for conducting temporally and ; spatially scaled ocean simulations driven by or are responsive to ocean models, and take into consideration coupling to atmospheric models; to continue the existing oceanographic/atmospheric data management task with emphasis on distributed databases in a network environment, with database optimization and standardization, including use of Mosaic and World Wide Web (WWW) access; and to implement a high performance parallel computing technology for CAST ocean models

Yeske, Lanny↗

NASA NTRS1997

A Java-Enabled Interactive Graphical Gas Turbine Propulsion System Simulator

This paper describes a gas turbine simulation system which utilizes the newly developed Java language environment software system. The system provides an interactive graphical environment which allows the quick and efficient construction and analysis of arbitrary gas turbine propulsion systems. The simulation system couples a graphical user interface, developed using the Java Abstract Window Toolkit, and a transient, space- averaged, aero-thermodynamic gas turbine analysis method, both entirely coded in the Java language. The combined package provides analytical, graphical and data management tools which allow the user to construct and control engine simulations by manipulating graphical objects on the computer display screen. Distributed simulations, including parallel processing and distributed database access across the Internet and World-Wide Web (WWW), are made possible through services provided by the Java environment.

Reed, John A.↗

NASA NTRS1999

Aerospace Engineering Systems

Continuous improvement of aerospace product development processes is a driving requirement across much of the aerospace community. As up to 90% of the cost of an aerospace product is committed during the first 10% of the development cycle, there is a strong emphasis on capturing, creating, and communicating better information (both requirements and performance) early in the product development process. The community has responded by pursuing the development of computer-based systems designed to enhance the decision-making capabilities of product development individuals and teams. Recently, the historical foci on sharing the geometrical representation and on configuration management are being augmented: Physics-based analysis tools for filling the design space database; Distributed computational resources to reduce response time and cost; Web-based technologies to relieve machine-dependence; and Artificial intelligence technologies to accelerate processes and reduce process variability. Activities such as the Advanced Design Technologies Testbed (ADTT) project at NASA Ames Research Center study the strengths and weaknesses of the technologies supporting each of these trends, as well as the overall impact of the combination of these trends on a product development event. Lessons learned and recommendations for future activities will be reported.

VanDalsem, William R.↗

NASA NTRS2002

The D3 Middleware Architecture

DARWIN is a NASA developed, Internet-based system for enabling aerospace researchers to securely and remotely access and collaborate on the analysis of aerospace vehicle design data, primarily the results of wind-tunnel testing and numeric (e.g., computational fluid-dynamics) model executions. DARWIN captures, stores and indexes data; manages derived knowledge (such as visualizations across multiple datasets); and provides an environment for designers to collaborate in the analysis of test results. DARWIN is an interesting application because it supports high-volumes of data. integrates multiple modalities of data display (e.g., images and data visualizations), and provides non-trivial access control mechanisms. DARWIN enables collaboration by allowing not only sharing visualizations of data, but also commentary about and views of data. Here we provide an overview of the architecture of D3, the third generation of DARWIN. Earlier versions of DARWIN were characterized by browser-based interfaces and a hodge-podge of server technologies: CGI scripts, applets, PERL, and so forth. But browsers proved difficult to control, and a proliferation of computational mechanisms proved inefficient and difficult to maintain. D3 substitutes a pure-Java approach for that medley: A Java client communicates (though RMI over HTTPS) with a Java-based application server. Code on the server accesses information from JDBC databases, distributed LDAP security services, and a collaborative information system. D3 is a three tier-architecture, but unlike 'E-commerce' applications, the data usage pattern suggests different strategies than traditional Enterprise Java Beans - we need to move volumes of related data together, considerable processing happens on the client, and the 'business logic' on the server-side is primarily data integration and collaboration. With D3, we are extending DARWIN to handle other data domains and to be a distributed system, where a single login allows a user transparent access to test results from multiple servers and authority domains.

Walton, Joan↗

NASA NTRS2005

Virtual Observatory Science Applications

Many Virtual-Observatory-based applications are now available to astronomers for use in their research. These span data discovery, access, visualization and analysis. Tools can quickly gather and organize information from sites around the world to help in planning a response to a gamma-ray burst, help users pick filters to isolate a desired feature, make an average template for z=2 AGN, select sources based upon information in many catalogs, or correlate massive distributed databases. Using VO protocols, the reach of existing software tools and packages can be greatly extended, allowing users to find and access remote information almost as conveniently as local data. The talk highlights just a few of the tools available to scientists, describes how both large and small scale projects can use existing tools, and previews some of the new capabilities that will be available in the next few years.

McGlynn, Tom↗

NASA NTRS2004

Discrepancy Reporting Management System

Discrepancy Reporting Management System (DRMS) is a computer program designed for use in the stations of NASA's Deep Space Network (DSN) to help establish the operational history of equipment items; acquire data on the quality of service provided to DSN customers; enable measurement of service performance; provide early insight into the need to improve processes, procedures, and interfaces; and enable the tracing of a data outage to a change in software or hardware. DRMS is a Web-based software system designed to include a distributed database and replication feature to achieve location-specific autonomy while maintaining a consistent high quality of data. DRMS incorporates commercial Web and database software. DRMS collects, processes, replicates, communicates, and manages information on spacecraft data discrepancies, equipment resets, and physical equipment status, and maintains an internal station log. All discrepancy reports (DRs), Master discrepancy reports (MDRs), and Reset data are replicated to a master server at NASA's Jet Propulsion Laboratory; Master DR data are replicated to all the DSN sites; and Station Logs are internal to each of the DSN sites and are not replicated. Data are validated according to several logical mathematical criteria. Queries can be performed on any combination of data.

Cooper, Tonja M.↗

NASA NTRS2016

Implementing Connected Component Labeling as a User Defined Operator for SciDB

We have implemented a flexible User Defined Operator (UDO) for labeling connected components of a binary mask expressed as an array in SciDB, a parallel distributed database management system based on the array data model. This UDO is able to process very large multidimensional arrays by exploiting SciDB's memory management mechanism that efficiently manipulates arrays whose memory requirements far exceed available physical memory. The UDO takes as primary inputs a binary mask array and a binary stencil array that specifies the connectivity of a given cell to its neighbors. The UDO returns an array of the same shape as the input mask array with each foreground cell containing the label of the component it belongs to. By default, dimensions are treated as non-periodic, but the UDO also accepts optional input parameters to specify periodicity in any of the array dimensions. The UDO requires four stages to completely label connected components. In the first stage, labels are computed for each subarray or chunk of the mask array in parallel across SciDB instances using the weighted quick union (WQU) with half-path compression algorithm. In the second stage, labels around chunk boundaries from the first stage are stored in a temporary SciDB array that is then replicated across all SciDB instances. Equivalences are resolved by again applying the WQU algorithm to these boundary labels. In the third stage, relabeling is done for each chunk using the resolved equivalences. In the fourth stage, the resolved labels, which so far are "flattened" coordinates of the original binary mask array, are renamed with sequential integers for legibility. The UDO is demonstrated on a 3-D mask of O(1011) elements, with O(108) foreground cells and O(106) connected components. The operator completes in 19 minutes using 84 SciDB instances.

UDO↗

DOE OSTI2021

The Effect of Spectral Resolution of Light Sources on Photopic and a-opic Quantities

There is a growing interest in including light source spectrum in advanced lighting software tools and simulations. Given that traditional lighting software tools have been used primarily for calculating photometric quantities, their simplifying assumptions may not be suitable for calculating other a-opic quantities. Commonly used simulation tools use three values to represent the three primary colors (red, green, and blue), but others have expanded the number of bands (i.e., the spectral resolution) to 9, 27, or 81 in an attempt to more accurately represent variations in light source spectrum and downstream spectrally-derived quantities. It remains unclear, however, to what extent spectral resolution affects calculated quantities. To address this gap, a numerical analysis was completed using a large spectral power distribution database (n = 1,302 light sources). Calculated illuminance, a-opic irradiance, luminous efficacy of radiation (LER), melanopic efficacy of radiation (MER), and melanopic to photopic (M/P) ratio were compared for spectral resolutions of 3 and 9 bands compared to a baseline of 81 bands. Across all examined lighting quantities, considerable errors—a mean absolute percent error of 18.4%—were found when using 3 band calculations. These were reduced to 4% for 9 band calculations. The errors varied by metric and light source type. The results suggest that the use of 9 bands can more accurately characterize performance of different light source types across a range of metrics compared to using 3 bands.

Abboushi, Belal K.↗

NASA NTRS1994

ARACHNID: A prototype object-oriented database tool for distributed systems

This paper discusses the results of a Phase 2 SBIR project sponsored by NASA and performed by MIMD Systems, Inc. A major objective of this project was to develop specific concepts for improved performance in accessing large databases. An object-oriented and distributed approach was used for the general design, while a geographical decomposition was used as a specific solution. The resulting software framework is called ARACHNID. The Faint Source Catalog developed by NASA was the initial database testbed. This is a database of many giga-bytes, where an order of magnitude improvement in query speed is being sought. This database contains faint infrared point sources obtained from telescope measurements of the sky. A geographical decomposition of this database is an attractive approach to dividing it into pieces. Each piece can then be searched on individual processors with only a weak data linkage between the processors being required. As a further demonstration of the concepts implemented in ARACHNID, a tourist information system is discussed. This version of ARACHNID is the commercial result of the project. It is a distributed, networked, database application where speed, maintenance, and reliability are important considerations. This paper focuses on the design concepts and technologies that form the basis for ARACHNID.

Younger, Herbert↗

DOE OSTI2022

Distributed Wind Project Database

The PNNL research team continually collects cost, incentive, generation, and customer data from turbine manufacturers, operations and maintenance providers, state and federal agencies, and other stakeholders for distributed wind projects installed in the United States. These data are critical for identifying trends, opportunities for growth, and prioritizing investments for both WETO and industry stakeholders. Making this information available allows interested parties to better understand distributed wind market trends and characteristics.

17 WIND ENERGY↗

NASA NTRS1992

Integrating a local database into the StarView distributed user interface

A distributed user interface to the Space Telescope Data Archive and Distribution Service (DADS) known as StarView is being developed. The DADS architecture consists of the data archive as well as a relational database catalog describing the archive. StarView is a client/server system in which the user interface is the front-end client to the DADS catalog and archive servers. Users query the DADS catalog from the StarView interface. Query commands are transmitted via a network and evaluated by the database. The results are returned via the network and are displayed on StarView forms. Based on the results, users decide which data sets to retrieve from the DADS archive. Archive requests are packaged by StarView and sent to DADS, which returns the requested data sets to the users. The advantages of distributed client/server user interfaces over traditional one-machine systems are well known. Since users run software on machines separate from the database, the overall client response time is much faster. Also, since the server is free to process only database requests, the database response time is much faster. Disadvantages inherent in this architecture are slow overall database access time due to the network delays, lack of a 'get previous row' command, and that refinements of a previously issued query must be submitted to the database server, even though the domain of values have already been returned by the previous query. This architecture also does not allow users to cross correlate DADS catalog data with other catalogs. Clearly, a distributed user interface would be more powerful if it overcame these disadvantages. A local database is being integrated into StarView to overcome these disadvantages. When a query is made through a StarView form, which is often composed of fields from multiple tables, it is translated to an SQL query and issued to the DADS catalog. At the same time, a local database table is created to contain the resulting rows of the query. The returned rows are displayed on the form as well as inserted into the local database table. Identical results are produced by reissuing the query to either the DADS catalog or to the local table. Relational databases do not provide a 'get previous row' function because of the inherent complexity of retrieving previous rows of multiple-table joins. However, since this function is easily implemented on a single table, StarView uses the local table to retrieve the previous row. Also, StarView issues subsequent query refinements to the local table instead of the DADS catalog, eliminating the network transmission overhead. Finally, other catalogs can be imported into the local database for cross correlation with local tables. Overall, it is believe that this is a more powerful architecture for distributed, database user interfaces.

Silberberg, D. P.↗

NASA NTRSDate not supplied

Distribution of SLS Integrated Load Uncertainty to Surface Pressures and Sectional Loads

Aerodynamic loads that are important to launch vehicle programs such as NASA’s Space Launch System (SLS) include both integrated loads such as the force & moment on the entire vehicle and distributed loads. In this work two examples of distributed loads are considered: the pressure field on the surface of the vehicle and sectional loads, which are one-dimensional distributions along the axis of the launch vehicle. In some modern flight programs, the integrated loads, such as lift and drag, used to design the guidance and control laws for the vehicle come from wind tunnel testing, while distributed loads are produced using Computational Fluid Dynamics(CFD). The first task that is addressed in this paper, then, is to provide a formal method to adjust the distributed loads so that integrating them matches the prescribed integrated load. In addition, the integrated loads in a launch vehicle typically include an uncertainty estimate. The second task is to distribute this prescribed integrated uncertainty to each point in a distributed load. Both tasks are addressed using the same technique, which is to create distributed load profiles that isolate adjustments to one integrated load while leaving the others unaffected. These adjustments are informed by Proper Orthogonal Decomposition (POD) of the entire CFD-based distributed load database. Once applied, the adjusted distributed loads can be used to evaluate any scalar quantity of interest that might be needed by downstream users such as structural analysis or trajectory modelers.

SLS↗

NASA NTRS1995

Mapper: A distributed object-oriented database application

This paper discusses the results of a Small Business Innovation Research (SBIR) project. The initial application involved decomposition of a large database across multiple processors to improve the speed of processing compound queries. The commercial outcome was a tourist information system with a point-to-point driving direction program called MAPPER. A distributed, object-oriented approach was used for the general design, while a spatial decomposition was used to divide the database into computationally manageable pieces. The resulting system is highly flexible with respect to both modifications and reuse.

Younger, Herbert↗

NASA NTRS1999

A Neural Network Aero Design System for Advanced Turbo-Engines

An inverse design method calculates the blade shape that produces a prescribed input pressure distribution. By controlling this input pressure distribution the aerodynamic design objectives can easily be met. Because of the intrinsic relationship between pressure distribution and airfoil physical properties, a Neural Network can be trained to choose the optimal pressure distribution that would meet a set of physical requirements. Neural network systems have been attempted in the context of direct design methods. From properties ascribed to a set of blades the neural network is trained to infer the properties of an 'interpolated' blade shape. The problem is that, especially in transonic regimes where we deal with intrinsically non linear and ill posed problems, small perturbations of the blade shape can produce very large variations of the flow parameters. It is very unlikely that, under these circumstances, a neural network will be able to find the proper solution. The unique situation in the present method is that the neural network can be trained to extract the required input pressure distribution from a database of pressure distributions while the inverse method will still compute the exact blade shape that corresponds to this 'interpolated' input pressure distribution. In other words, the interpolation process is transferred to a smoother problem, namely, finding what pressure distribution would produce the required flow conditions and, once this is done, the inverse method will compute the exact solution for this problem. The use of neural network is, in this context, highly related to the use of proper optimization techniques. The optimization is used essentially as an automation procedure to force the input pressure distributions to achieve the required aero and structural design parameters. A multilayered feed forward network with back-propagation is used to train the system for pattern association and classification.

Sanz, Jose M.↗