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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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NASA NTRS1992

A modular software system for distributed telerobotics

The authors describe a control architecture for telerobotics research. The architecture was object-oriented and data-driven, and can be distributed over many processors on a wide-area network (WAN). The basic capabilities of this testbed have already been demonstrated in tests distributed over four cities. The data distribution techniques of this control architecture are described, as well as details of the current implementation and experimental results.

Graves, Sean↗

NASA NTRS1995

Achieving reutilization of scheduling software through abstraction and generalization

Reutilization of software is a difficult goal to achieve particularly in complex environments that require advanced software systems. The Request-Oriented Scheduling Engine (ROSE) was developed to create a reusable scheduling system for the diverse scheduling needs of the National Aeronautics and Space Administration (NASA). ROSE is a data-driven scheduler that accepts inputs such as user activities, available resources, timing contraints, and user-defined events, and then produces a conflict-free schedule. To support reutilization, ROSE is designed to be flexible, extensible, and portable. With these design features, applying ROSE to a new scheduling application does not require changing the core scheduling engine, even if the new application requires significantly larger or smaller data sets, customized scheduling algorithms, or software portability. This paper includes a ROSE scheduling system description emphasizing its general-purpose features, reutilization techniques, and tasks for which ROSE reuse provided a low-risk solution with significant cost savings and reduced software development time.

Wilkinson, George J.↗

NASA NTRS1986

Design considerations for flight test of a fault inferring nonlinear detection system algorithm for avionics sensors

This paper summarizes the modifications made to the design of a fault inferring nonlinear detection system (FINDS) algorithm to accommodate flight computer constraints and the resulting impact on the algorithm performance. An overview of the flight data-driven FINDS algorithm is presented. This is followed by a brief analysis of the effects of modifications to the algorithm on program size and execution speed. Significant improvements in estimation performance for the aircraft states and normal operating sensor biases, which have resulted from improved noise design parameters and a new steady-state wind model, are documented. The aircraft state and sensor bias estimation performances of the algorithm's extended Kalman filter are presented as a function of update frequency of the piecewise constant filter gains. The results of a new detection system strategy and failure detection performance, as a function of an update frequency, are also presented.

Caglayan, A. K.↗

NASA NTRS1986

Design considerations for flight test of a fault inferring nonlinear detection system algorithm for avionics sensors

The modifications to the design of a fault inferring nonlinear detection system (FINDS) algorithm to accommodate flight computer constraints and the resulting impact on the algorithm performance are summarized. An overview of the flight data-driven FINDS algorithm is presented. This is followed by a brief analysis of the effects of modifications to the algorithm on program size and execution speed. Significant improvements in estimation performance for the aircraft states and normal operating sensor biases, which have resulted from improved noise design parameters and a new steady-state wind model, are documented. The aircraft state and sensor bias estimation performances of the algorithm's extended Kalman filter are presented as a function of update frequency of the piecewise constant filter gains. The results of a new detection system strategy and failure detection performance, as a function of gain update frequency, are also presented.

Caglayan, A. K.↗

NASA NTRS2003

Vector-Ordering Filter Procedure for Data Reduction

The vector-ordering filter (VOF) technique involves a procedure for sampling a large population of data vectors to select a subset of data vectors that fully characterize the state space of the large population. The VOF technique enables a large reduction of the volume of data that must be handled in the automated monitoring system and method discussed in the two immediately preceding articles. In so doing, the VOF technique enables the development of data-driven mathematical models of a monitored asset from sets of data that would otherwise exceed the memory capacities of conventional engineering computers. Data-driven mathematical models have been shown to offer high fidelity for purposes of control and monitoring of assets. In practice, a collection of asset-operating observations is acquired with the intention that the collection contain observations characteristic of the full dynamic range of operation of the asset. Often, such a collection contains an extremely large number of observations, many of which are redundant. The VOF technique fills the need for a means to extract, from the original collection of observational data, a reduced data matrix that excludes redundant data while maintaining the full statistical character and dynamic range of the original data. The reduced data matrix can then be used as the input data for development of a mathematical model of the monitored asset, or as training data for a neural-network substitute for an explicit mathematical model of the asset. Alternatively, the reduced data matrix can, itself, be used directly as a mathematical model of the monitored asset, as is commonly done in multivariate state-estimation techniques. The original data are collected from the asset over a range of operating states and are put in matrix form. Each column vector in the original data matrix represents the signal values acquired at a particular operational state of the asset. Thus, the number of columns of the original data matrix equals the number of observed states and the number of rows in this matrix equals the number of signals acquired at each observation. In the VOF technique, one extracts the reduced data matrix from the original data matrix through the selection of a representative subset of the column (state) vectors.

Bickford, Randall L.↗

NASA NTRS1994

Common spaceborne multicomputer operating system and development environment

A preliminary technical specification for a multicomputer operating system is developed. The operating system is targeted for spaceborne flight missions and provides a broad range of real-time functionality, dynamic remote code-patching capability, and system fault tolerance and long-term survivability features. Dataflow concepts are used for representing application algorithms. Functional features are included to ensure real-time predictability for a class of algorithms which require data-driven execution on an iterative steady state basis. The development environment supports the development of algorithm code, design of control parameters, performance analysis, simulation of real-time dataflow applications, and compiling and downloading of the resulting application.

Craymer, L. G.↗

NASA NTRS1992

Transportable Applications Environment (TAE) Plus: A NASA tool used to develop and manage graphical user interfaces

The Transportable Applications Environment (TAE) Plus was built to support the construction of graphical user interfaces (GUI's) for highly interactive applications, such as real-time processing systems and scientific analysis systems. It is a general purpose portable tool that includes a 'What You See Is What You Get' WorkBench that allows user interface designers to layout and manipulate windows and interaction objects. The WorkBench includes both user entry objects (e.g., radio buttons, menus) and data-driven objects (e.g., dials, gages, stripcharts), which dynamically change based on values of realtime data. Discussed here is what TAE Plus provides, how the implementation has utilized state-of-the-art technologies within graphic workstations, and how it has been used both within and without NASA.

Szczur, Martha R.↗

NASA NTRS2007

A Support Database System for Integrated System Health Management (ISHM)

The development, deployment, operation and maintenance of Integrated Systems Health Management (ISHM) applications require the storage and processing of tremendous amounts of low-level data. This data must be shared in a secure and cost-effective manner between developers, and processed within several heterogeneous architectures. Modern database technology allows this data to be organized efficiently, while ensuring the integrity and security of the data. The extensibility and interoperability of the current database technologies also allows for the creation of an associated support database system. A support database system provides additional capabilities by building applications on top of the database structure. These applications can then be used to support the various technologies in an ISHM architecture. This presentation and paper propose a detailed structure and application description for a support database system, called the Health Assessment Database System (HADS). The HADS provides a shared context for organizing and distributing data as well as a definition of the applications that provide the required data-driven support to ISHM. This approach provides another powerful tool for ISHM developers, while also enabling novel functionality. This functionality includes: automated firmware updating and deployment, algorithm development assistance and electronic datasheet generation. The architecture for the HADS has been developed as part of the ISHM toolset at Stennis Space Center for rocket engine testing. A detailed implementation has begun for the Methane Thruster Testbed Project (MTTP) in order to assist in developing health assessment and anomaly detection algorithms for ISHM. The structure of this implementation is shown in Figure 1. The database structure consists of three primary components: the system hierarchy model, the historical data archive and the firmware codebase. The system hierarchy model replicates the physical relationships between system elements to provide the logical context for the database. The historical data archive provides a common repository for sensor data that can be shared between developers and applications. The firmware codebase is used by the developer to organize the intelligent element firmware into atomic units which can be assembled into complete firmware for specific elements.

FROM↗

NASA NTRS1987

Computer architecture for efficient algorithmic executions in real-time systems: New technology for avionics systems and advanced space vehicles

Improvements and advances in the development of computer architecture now provide innovative technology for the recasting of traditional sequential solutions into high-performance, low-cost, parallel system to increase system performance. Research conducted in development of specialized computer architecture for the algorithmic execution of an avionics system, guidance and control problem in real time is described. A comprehensive treatment of both the hardware and software structures of a customized computer which performs real-time computation of guidance commands with updated estimates of target motion and time-to-go is presented. An optimal, real-time allocation algorithm was developed which maps the algorithmic tasks onto the processing elements. This allocation is based on the critical path analysis. The final stage is the design and development of the hardware structures suitable for the efficient execution of the allocated task graph. The processing element is designed for rapid execution of the allocated tasks. Fault tolerance is a key feature of the overall architecture. Parallel numerical integration techniques, tasks definitions, and allocation algorithms are discussed. The parallel implementation is analytically verified and the experimental results are presented. The design of the data-driven computer architecture, customized for the execution of the particular algorithm, is discussed.

Carroll, Chester C.↗

NASA NTRS1978

Processing by data and program blocks

A processing system is presented that implements simultaneously the efficiency of the special-purpose processor and the total applicability of the general-purpose computer - characteristics commonly thought of as being mutually exclusive. This is achieved through specializing the machine by programming the hardware structure, rather than by adding software systems to it. Data are organized in circulating pages which form a multiplicity of local dynamic memories for each process. Programs are made up of modules, each describing a transient special-purpose machine. A characteristic of this approach is that the processes are data-driven, rather than program-driven. The programming language presents significant flexibility and efficiency in modeling certain classes of problems, and it may be of interest as an implementation model in a broader context. Applications to real-time processing of radar signals are reported. The relevance of characteristics of this system to problems in multiprogramming and multiprocessing systems is discussed.

Schaffner, M. R.↗

NASA NTRS1989

Hyperswitch Network For Hypercube Computer

Data-driven dynamic switching enables high speed data transfer. Proposed hyperswitch network based on mixed static and dynamic topologies. Routing header modified in response to congestion or faults encountered as path established. Static topology meets requirement if nodes have switching elements that perform necessary routing header revisions dynamically. Hypercube topology now being implemented with switching element in each computer node aimed at designing very-richly-interconnected multicomputer system. Interconnection network connects great number of small computer nodes, using fixed hypercube topology, characterized by point-to-point links between nodes.

Chow, Edward↗

NASA NTRS1989

Real-Time MENTAT programming language and architecture

Real-time MENTAT, a programming environment designed to simplify the task of programming real-time applications in distributed and parallel environments, is described. It is based on the same data-driven computation model and object-oriented programming paradigm as MENTAT. It provides an easy-to-use mechanism to exploit parallelism, language constructs for the expression and enforcement of timing constraints, and run-time support for scheduling and exciting real-time programs. The real-time MENTAT programming language is an extended C++. The extensions are added to facilitate automatic detection of data flow and generation of data flow graphs, to express the timing constraints of individual granules of computation, and to provide scheduling directives for the runtime system. A high-level view of the real-time MENTAT system architecture and programming language constructs is provided.

Grimshaw, Andrew S.↗

NASA NTRS1992

Advanced software development workstation. Comparison of two object-oriented development methodologies

This report is an attempt to clarify some of the concerns raised about the OMT method, specifically that OMT is weaker than the Booch method in a few key areas. This interim report specifically addresses the following issues: (1) is OMT object-oriented or only data-driven?; (2) can OMT be used as a front-end to implementation in C++?; (3) the inheritance concept in OMT is in contradiction with the 'pure and real' inheritance concept found in object-oriented (OO) design; (4) low support for software life-cycle issues, for project and risk management; (5) uselessness of functional modeling for the ROSE project; and (6) problems with event-driven and simulation systems. The conclusion of this report is that both Booch's method and Rumbaugh's method are good OO methods, each with strengths and weaknesses in different areas of the development process.

Izygon, Michel E.↗

NASA NTRS1994

Graph-Based Dynamic Assignment Of Multiple Processors

Algorithm-to-architecture mapping model (ATAMM) is strategy minimizing time needed to periodically execute graphically described, data-driven application algorithm on multiple data processors. Implemented as operating system managing flow of data and dynamically assigns nodes of graph to processors. Predicts throughput versus number of processors available to execute given application algorithm. Includes rules ensuring application algorithm represented by graph executed periodically without deadlock and in shortest possible repetition time. ATAMM proves useful in maximizing effectiveness of parallel computing systems.

Hayes, Paul J.↗

NASA NTRS1992

Teamwork for Oversight of Processes and Systems (TOPS). Implementation guide for TOPS version 2.0, 10 August 1992

As the nation redefines priorities to deal with a rapidly changing world order, both government and industry require new approaches for oversight of management systems, particularly for high technology products. Declining defense budgets will lead to significant reductions in government contract management personnel. Concurrently, defense contractors are reducing administrative and overhead staffing to control costs. These combined pressures require bold approaches for the oversight of management systems. In the Spring of 1991, the DPRO and TRW created a Process Action Team (PAT) to jointly prepare a Performance Based Management (PBM) system titled Teamwork for Oversight of Processes and Systems (TOPS). The primary goal is implementation of a performance based management system based on objective data to review critical TRW processes with an emphasis on continuous improvement. The processes are: Finance and Business Systems, Engineering and Manufacturing Systems, Quality Assurance, and Software Systems. The team established a number of goals: delivery of quality products to contractual terms and conditions; ensure that TRW management systems meet government guidance and good business practices; use of objective data to measure critical processes; elimination of wasteful/duplicative reviews and audits; emphasis on teamwork--all efforts must be perceived to add value by both sides and decisions are made by consensus; and synergy and the creation of a strong working trust between TRW and the DPRO. TOPS permits the adjustment of oversight resources when conditions change or when TRW systems performance indicate either an increase or decrease in surveillance is appropriate. Monthly Contractor Performance Assessments (CPA) are derived from a summary of supporting system level and process-level ratings obtained from objective process-level data. Tiered, objective, data-driven metrics are highly successful in achieving a cooperative and effective method of measuring performance. The teamwork-based culture developed by TOPS proved an unequaled success in removing adversarial relationships and creating an atmosphere of continuous improvement in quality processes at TRW. The new working relationship does not decrease the responsibility or authority of the DPRO to ensure contract compliance and it permits both parties to work more effectively to improve total quality and reduce cost. By emphasizing teamwork in developing a stronger approach to efficient management of the defense industrial base TOPS is a singular success.

Strand, Albert A.↗

NASA NTRS1999

SIRTF Science Operations System Design

SIRTF Science Operations System Design William B. Green Manager, SIRTF Science Center California Institute of Technology M/S 310-6 1200 E. California Blvd., Pasadena CA 91125 (626) 395 8572 Fax (626) 568 0673 bgreen@ipac.caltech.edu. The Space Infrared Telescope Facility (SIRTF) will be launched in December 2001, and perform an extended series of science observations at wavelengths ranging from 20 to 160 microns for five years or more. The California Institute of Technology has been selected as the home for the SIRTF Science Center (SSC). The SSC will be responsible for evaluating and selecting observation proposals, providing technical support to the science community, performing mission planning and science observation scheduling activities, instrument calibration during operations and instrument health monitoring, production of archival quality data products, and management of science research grants. The science payload consists of three instruments delivered by instrument Principal Investigators located at University of Arizona, Cornell, and Harvard Smithsonian Astrophysical Observatory. The SSC is responsible for design, development, and operation of the Science Operations System (SOS) which will support the functions assigned to the SSC by NASA. The SIRTF spacecraft, mission profile, and science instrument design have undergone almost ten years of refinement. SIRTF development and operations activities are highly cost constrained. The cost constraints have impacted the design of the SOS in several ways. The Science Operations System has been designed to incorporate a set of efficient, easy to use tools which will make it possible for scientists to propose observation sequences in a rapid and automated manner. The use of highly automated tools for requesting observations will simplify the long range observatory scheduling process, and the short term scheduling of science observations. Pipeline data processing will be highly automated and data-driven, utilizing a variety of tools developed at JPL, the instrument development teams, and Space Telescope Science Institute to automate processing. An incremental ground data system development approach has been adopted, featuring periodic deliveries that are validated with the flight hardware throughout the various phases of system level development and testing. This approach minimizes development time and decreases operations risk. This paper will describe the top level architecture of the SOS and the basic design concepts. A summary of the incremental development approach will be presented. Examples of the unique science user tools now under final development prior to the first proposal call scheduled for mid-2000 will be shown.

Green, William↗

NASA NTRS2004

Model-Biased, Data-Driven Adaptive Failure Prediction

This final report, which contains a research summary and a viewgraph presentation, addresses clustering and data simulation techniques for failure prediction. The researchers applied their techniques to both helicopter gearbox anomaly detection and segmentation of Earth Observing System (EOS) satellite imagery.

Leen, Todd K.↗

NASA NTRS2007

Simple, Script-Based Science Processing Archive

The Simple, Scalable, Script-based Science Processing (S4P) Archive (S4PA) is a disk-based archival system for remote sensing data. It is based on the data-driven framework of S4P and is used for data transfer, data preprocessing, metadata generation, data archive, and data distribution. New data are automatically detected by the system. S4P provides services such as data access control, data subscription, metadata publication, data replication, and data recovery. It comprises scripts that control the data flow. The system detects the availability of data on an FTP (file transfer protocol) server, initiates data transfer, preprocesses data if necessary, and archives it on readily available disk drives with FTP and HTTP (Hypertext Transfer Protocol) access, allowing instantaneous data access. There are options for plug-ins for data preprocessing before storage. Publication of metadata to external applications such as the Earth Observing System Clearinghouse (ECHO) is also supported. S4PA includes a graphical user interface for monitoring the system operation and a tool for deploying the system. To ensure reliability, S4P continuously checks stored data for integrity, Further reliability is provided by tape backups of disks made once a disk partition is full and closed. The system is designed for low maintenance, requiring minimal operator oversight.

Lynnes, Christopher↗