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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Development and implementation of a programmable telemetry processor

A programmable telemetry processor was designed for the NASA Goddard Space Flight Center in support of the Systems Utilization Enhancement (SUE) upgrade of the NASA tracking stations at Merritt Island, FL, and Bermuda. The processor is an integrated hardware and software system that performs the front-end telemetry synchronization and decommutation functions and provides for application-specific data processing. This paper presents the design, architecture, and features of the microprocessor controlled unit.

Flagg, Howard S.↗
NASA NTRS2005

Visions of Automation and Realities of Certification

Quite a lot of people envision automation as the solution to many of the problems in aviation and air transportation today, across all sectors: commercial, private, and military. This paper explains why some recent experiences with complex, highly-integrated, automated systems suggest that this vision will not be realized unless significant progress is made over the current state-of-the-practice in software system development and certification.

Hayhurst, Kelly J.↗
NASA NTRS2014

A New Global Regression Analysis Method for the Prediction of Wind Tunnel Model Weight Corrections

A new global regression analysis method is discussed that predicts wind tunnel model weight corrections for strain-gage balance loads during a wind tunnel test. The method determines corrections by combining "wind-on" model attitude measurements with least squares estimates of the model weight and center of gravity coordinates that are obtained from "wind-off" data points. The method treats the least squares fit of the model weight separate from the fit of the center of gravity coordinates. Therefore, it performs two fits of "wind- off" data points and uses the least squares estimator of the model weight as an input for the fit of the center of gravity coordinates. Explicit equations for the least squares estimators of the weight and center of gravity coordinates are derived that simplify the implementation of the method in the data system software of a wind tunnel. In addition, recommendations for sets of "wind-off" data points are made that take typical model support system constraints into account. Explicit equations of the confidence intervals on the model weight and center of gravity coordinates and two different error analyses of the model weight prediction are also discussed in the appendices of the paper.

strain-gage balance↗
NASA NTRS2019

"Sensor Web Evolution - Webs of Webs for NASA Science - Focus on small Uninhabited Aerial Systems (sUAS)"

This paper will describe the evolution of information collection, derivation and delivery mechanisms in webs of NASA sensor webs, with a focus on recent advancements in small Uninhabited Aerial Systems (sUAS). I will discuss the movement to "Fog Computing", also known as Edge Computing. Fog Computing facilitates the distribution of common operations and networking between edge devices and cloud computing facilities, optimizing the production of actionable intelligence. Initially, sUASs utilized onboard data collection as standard, with minimal data downloaded directly. Information products were derived in conventional computational environments, generally desk top computers, and information products made available to the Science Community in weeks or months. With the increased availability, and increasingly lower costs, of beyond line of sight (BLOS) satellite based communication, transmission rates and data volumes increased, and processing migrated to Cloud based services. Contemporary sUASs are moving some of that information product derivation to on vehicle services, and are creating a distributed Cloud/Fog environment. I will describe the technological advances that have made this possible, including low power multi-core Central Processing Units (CPU), and, more recently, the availability of high end Graphical Processing Units (GPU) that consume only a few watts. Intelligent system software, leveraging these hardware advances, finally allows for information product generation on-board, rather than simple data collection. Additionally, intelligent flight control systems now support mutual vehicle to vehicle collaboration, allowing sUASs to create ad-hoc sensor webs on demand, as required. Also discussed will be the lessons learned by the Authors' development of data systems for NASA's large High Altitude Long Endurance (HALE) UASs like Predator and Global Hawk, and how those lessons are being applied to sUAS development. This paper will focus on application, rather a deep dive into the technology, and will highlight improving data management through these new technologies.

Sensor Web↗
NASA NTRSDate not supplied

UASs in the VOG/Edge/FOG Sensor Web Environment

This paper will describe the evolution of information collection, derivation and delivery mechanisms in sensor webs utilizing Uninhabited Aerial Systems (UAS).We will discuss the movement to "Fog Computing", also known as Edge Computing. Fog Computing facilitates the distribution of common operations and networking between edge devices and cloud computing facilities, optimizing the production of actionable intelligence. Initially, UASs utilized onboard data collection as standard, with minimal data downloaded directly. Information products were derived in conventional computational environments, generally desk top computers, and information products made available to the Science Community in weeks or months. With the increased availability, and increasingly lower costs, of beyond line of sight (BLOS) satellite based communication, transmission rates and data volumes increased, and processing migrated to Cloud based services. Contemporary UASs are moving some of that information product derivation to on vehicle services, and are creating a distributed Cloud/Fog environment. The Author will describe the technological advances that have made this possible, including low power multi-core Central Processing Units (CPU), and, more recently, the availability of high end Graphical Processing Units (GPU) that consume only a few watts. Intelligent system software, leveraging these hardware advances, finally allows for information product generation on-board, rather than simple data collection. Additionally, intelligent flight control systems now support mutual vehicle to vehicle collaboration, allowing UASs to create ad-hoc sensor webs on demand, as required. Also discussed will be the lessons learned by the Authors' development of data systems for NASA's large High Altitude Long Endurance (HALE) UASs like Predator and Global Hawk, and how those lessons are being applied to other UAS development This paper will focus on applications, rather a deep dive into the technology, and will highlight improving data management through these new technologies.

UAS↗
NASA NTRS2006

AERCam Autonomy: Intelligent Software Architecture for Robotic Free Flying Nanosatellite Inspection Vehicles

The NASA Johnson Space Center has developed a nanosatellite-class Free Flyer intended for future external inspection and remote viewing of human spacecraft. The Miniature Autonomous Extravehicular Robotic Camera (Mini AERCam) technology demonstration unit has been integrated into the approximate form and function of a flight system. The spherical Mini AERCam Free Flyer is 7.5 inches in diameter and weighs approximately 10 pounds, yet it incorporates significant additional capabilities compared to the 35-pound, 14-inch diameter AERCam Sprint that flew as a Shuttle flight experiment in 1997. Mini AERCam hosts a full suite of miniaturized avionics, instrumentation, communications, navigation, power, propulsion, and imaging subsystems, including digital video cameras and a high resolution still image camera. The vehicle is designed for either remotely piloted operations or supervised autonomous operations, including automatic stationkeeping, point-to-point maneuvering, and waypoint tracking. The Mini AERCam Free Flyer is accompanied by a sophisticated control station for command and control, as well as a docking system for automated deployment, docking, and recharge at a parent spacecraft. Free Flyer functional testing has been conducted successfully on both an airbearing table and in a six-degree-of-freedom closed-loop orbital simulation with avionics hardware in the loop. Mini AERCam aims to provide beneficial on-orbit views that cannot be obtained from fixed cameras, cameras on robotic manipulators, or cameras carried by crewmembers during extravehicular activities (EVA s). On Shuttle or International Space Station (ISS), for example, Mini AERCam could support external robotic operations by supplying orthogonal views to the intravehicular activity (IVA) robotic operator, supply views of EVA operations to IVA and/or ground crews monitoring the EVA, and carry out independent visual inspections of areas of interest around the spacecraft. To enable these future benefits with minimal impact on IVA operators and ground controllers, the Mini AERCam system architecture incorporates intelligent systems attributes that support various autonomous capabilities. 1) A robust command sequencer enables task-level command scripting. Command scripting is employed for operations such as automatic inspection scans over a region of interest, and operator-hands-off automated docking. 2) A system manager built on the same expert-system software as the command sequencer provides detection and smart-response capability for potential system-level anomalies, like loss of communications between the Free Flyer and control station. 3) An AERCam dynamics manager provides nominal and off-nominal management of guidance, navigation, and control (GN&C) functions. It is employed for safe trajectory monitoring, contingency maneuvering, and related roles. This paper will describe these architectural components of Mini AERCam autonomy, as well as the interaction of these elements with a human operator during supervised autonomous control.

Fredrickson, Steven E.↗
NASA NTRS1997

Novel software for analysis of root gravitropism: comparative response patterns of Arabidopsis wild-type and axr1 seedlings

In an earlier study (Evans, Ishikawa & Estelle 1994, Planta 194, 215-222) we used a video digitizer system to compare the kinetics of auxin action on root elongation in wild-type seedlings and seedlings of auxin response mutants of Arabidopsis thaliana (L.) Heynh. We have since modified the system software to allow determination of elongation on opposite sides of vertical or gravistimulated roots and to allow continuous measurement of the angle of orientation of sequential subsections of the root during the response. We used this technology to compare the patterns of differential growth that generate curvature in roots of the Columbia ecotype and in the mutants axr1-3, axr1-12 and axr2, which show reduced gravitropic responsiveness and reduced sensitivity to inhibition by auxin. The pattern of differential growth during gravitropism differed in roots of wild-type and axr1 seedlings. In wild-type roots, initial curvature resulted from differential inhibition of elongation in the distal elongation zone (DEZ). This was followed by an acceleration of elongation along the top side of the DEZ. In roots of axr1-3, curvature resulted from differential stimulation of elongation whereas in roots of axr1-12 the response was variable. Roots of axr2 did not exhibit gravitropic curvature. The observation that the pattern of differential growth causing curvature is dramatically altered by a change in sensitivity to auxin is consistent with the classical Cholodny-Went theory of gravitropism which maintains that differential growth patterns induced by gravistimulation are mediated primarily by gravi-induced shifts in auxin distribution. The new technology introduced with this report allows automated determination of stimulus response patterns in the small but experimentally popular roots of Arabidopsis.

Non-NASA Center↗
NASA NTRS2002

REACH: Real-Time Data Awareness in Multi-Spacecraft Missions

Missions have been proposed that will use multiple spacecraft to perform scientific or commercial tasks. Indeed, in the commercial world, some spacecraft constellations already exist. Aside from the technical challenges of constructing and flying these missions, there is also the financial challenge presented by the tradition model of the flight operations team (FOT) when it is applied to a constellation mission. Proposed constellation missions range in size from three spacecraft to more than 50. If the current ratio of three-to-five FOT personnel per spacecraft is maintained, the size of the FOT becomes cost prohibitive. The Advanced Architectures and Automation Branch at the Goddard Space Flight Center (GSFC Code 588) saw the potential to reduce the cost of these missions by creating new user interfaces to the ground system health-and-safety data. The goal is to enable a smaller FOT to remain aware and responsive to the increased amount of ground system information in a multi-spacecraft environment. Rather than abandon the tried and true, these interfaces were developed to run alongside existing ground system software to provide additional support to the FOT. These new user interfaces have been combined in a tool called REACH. REACH-the Real-time Evaluation and Analysis of Consolidated Health-is a software product that uses advanced visualization techniques to make spacecraft anomalies easy to spot, no matter how many spacecraft are in the constellation. REACH reads a real-time stream of data from the ground system and displays it to the FOT such that anomalies are easy to pick out and investigate. Data visualization has been used in ground system operations for many years. To provide a unique visualization tool, we developed a unique source of data to visualize: the REACH Health Model Engine. The Health Model Engine is rule-based software that receives real-time telemetry information and outputs "health" information related to the subsystems and spacecraft that the telemetry belong to. The Health Engine can run out-of-the-box or can be tailored with a scripting language. Out of the box, it uses limit violations to determine the health of subsystems and spacecraft; when tailored, it determines health using equations combining the values and limits of any telemetry in the spacecraft. The REACH visualizations then "roll up" the information from the Health Engine into high level, summary displays. These summary visualizations can be "zoomed" into for increasing levels of detail. Currently REACH is installed in the Small Explorer (SMEX) lab at GSFC, and is monitoring three of their five spacecraft. We are scheduled to install REACH in the Mid-sized Explorer (MIDEX) lab, which will allow us to monitor up to six more spacecraft. The process of installing and using our "research" software in an operational environment has provided many insights into which parts of REACH are a step forward and which of our ideas are missteps. Our paper explores both the new concepts in spacecraft health-and-safety visualization, the difficulties of such systems in the operational environment, and the cost and safety issues of multi-spacecraft missions.

Maks, Lori↗
DOE OSTI2014

There goes the neighborhood: performance degradation due to nearby jobs

Predictable performance is important for understanding and alleviating application performance issues; quantifying the effects of source code, compiler, or system software changes; estimating the time required for batch jobs; and determining the allocation requests for proposals. Our experiments show that on a Cray XE system, the execution time of a communication-heavy parallel application ranges from 28% faster to 41% slower than the average observed performance. Blue Gene systems, on the other hand, demonstrate no noticeable run-to-run variability. In this paper, we focus on Cray machines and investigate potential causes for performance variability such as OS jitter, shape of the allocated partition, and interference from other jobs sharing the same network links. Reducing such variability could improve overall throughput at a computer center and save energy costs.

Computer Science↗
DOE OSTI2019

Results of the Collaborative International Evaluated Library Organization (CIELO) Project

Simulation of nuclear systems requires complete data that represents the relevant nuclear physics. This requires many types of experimental measurements, theoretical physics, semi-empirical models and software systems, as well as experts to integrate and guide the process. This discipline is collectively known as nuclear data, and separate programmes within various European countries, the USA, Japan, Russia, and other OECD Nuclear Energy Agency (NEA) member countries have been operating for many decades. The NEA Working Party on International Nuclear Data Evaluation Co-operation (WPEC) exists to improve the quality and completeness of nuclear data by bringing together representatives of the major nuclear data evaluation projects of NEA member countries and selected Invitees. The Sub- and Expert Groups of the WPEC typically focus on specific technical topics, while the Collaborative International Evaluated Library Organisation Pilot Project (CIELO) was established to generate complete evaluations for a selection of the most important isotopes for criticality in nuclear technologies: 235,238 U, 239 Pu, 56 Fe, 16 O and 1 H.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1978

On improved ranging

The use of a 1 MHz range code and a narrow-passband IF filter reduces waveform distortion error by a factor of as much as 20. Along with this improvement in ranging precision, ranging accuracy is enhanced by nullifying many errors caused by equipment vagaries. The IF filter and concomitant modification of ranging system software (and in the case of the planetary ranging assembly, hardware) are the most cost-effective way of improving the current generation ranging system.

Layland, J. W.↗
NASA NTRS1985

Design of Multivariable Controllers Using the Integrated Analysis Capability (IAC)

Dynamic analysis and controls design for flexible spacecraft involves high-order dynamic systems with multiple inputs and outputs. Computer tools are essential for such analysis. The controls/structures interaction analysis capability of an inter-disciplinary computer software system, called the Integrated Analysis Capability (IAC), is described. An overview of IAC components and procedures is presented, and an example of a preliminary space station controls design is shown.

Bossi, J. A.↗
NASA NTRS1989

AdaNET phase 0 support for the AdaNET Dynamic Software Inventory (DSI) management system prototype. Catalog of available reusable software components

The Ada Software Repository is a public-domain collection of Ada software and information. The Ada Software Repository is one of several repositories located on the SIMTEL20 Defense Data Network host computer at White Sands Missile Range, and available to any host computer on the network since 26 November 1984. This repository provides a free source for Ada programs and information. The Ada Software Repository is divided into several subdirectories. These directories are organized by topic, and their names and a brief overview of their topics are contained. The Ada Software Repository on SIMTEL20 serves two basic roles: to promote the exchange and use (reusability) of Ada programs and tools (including components) and to promote Ada education.

Hanley, Lionel↗
NASA NTRS1996

High Stability Engine Control (HISTEC)

Future aircraft turbine engines, both commercial and military, must be able to successfully accommodate expected increased levels of steady-state and dynamic engine-face distortion. The current approach of incorporating a sufficient component design stall margin to tolerate these increased levels of distortion would significantly reduce performance. The objective of the High Stability Engine Control (HISTEC) program is to design, develop, and flight demonstrate an advanced, high-stability, integrated engine control system that uses measurement-based, real-time estimates of distortion to enhance engine stability. The resulting distortion tolerant control reduces the required design stall margin, with a corresponding increase in performance and decrease in fuel burn. The HISTEC concept, consisting of a Distortion Estimation System and a Stability Management Control, has been designed and developed. The Distortion Estimation System uses a small number of high-response pressure sensors at the engine face to calculate indicators of the type and extent of distortion in real time. The Stability Management Control, through direct control of the fan and compressor pressure ratio, accommodates the distortion by transiently increasing the amount of stall margin available based on information from the Distortion Estimation System. Simulation studies have shown the HISTEC distortion tolerant control is able to successfully estimate and accommodate time-varying distortion. Currently, hardware and software systems necessary for flight demonstration of the HISTEC concept are being designed and developed. The HISTEC concept will be flight tested in early 1997.

DeLaat, John C.↗
NASA NTRS2005

A unifying framework for systems modeling, control systems design, and system operation

Current engineering practice in the analysis and design of large-scale multi-disciplinary control systems is typified by some form of decomposition- whether functional or physical or discipline-based-that enables multiple teams to work in parallel and in relative isolation. Too often, the resulting system after integration is an awkward marriage of different control and data mechanisms with poor end-to-end accountability. System of systems engineering, which faces this problem on a large scale, cries out for a unifying framework to guide analysis, design, and operation. This paper describes such a framework based on a state-, model-, and goal-based architecture for semi-autonomous control systems that guides analysis and modeling, shapes control system software design, and directly specifies operational intent. This paper illustrates the key concepts in the context of a large-scale, concurrent, globally distributed system of systems: NASA's proposed Array-based Deep Space Network.

systems modeling↗
NASA NTRS2009

Framework for ReSTful Web Services in OSGi

Ensemble ReST is a software system that eases the development, deployment, and maintenance of server-side application programs to perform functions that would otherwise be performed by client software. Ensemble ReST takes advantage of the proven disciplines of ReST (Representational State Transfer. ReST leverages the standardized HTTP protocol to enable developers to offer services to a diverse variety of clients: from shell scripts to sophisticated Java application suites

Shams, Khawaja S.↗
NASA NTRS1994

Reengineering legacy software to object-oriented systems

NASA has a legacy of complex software systems that are becoming increasingly expensive to maintain. Reengineering is one approach to modemizing these systems. Object-oriented technology, other modem software engineering principles, and automated tools can be used to reengineer the systems and will help to keep maintenance costs of the modemized systems down. The Software Technology Branch at the NASA/Johnson Space Center has been developing and testing reengineering methods and tools for several years. The Software Technology Branch is currently providing training and consulting support to several large reengineering projects at JSC, including the Reusable Objects Software Environment (ROSE) project, which is reengineering the flight analysis and design system (over 2 million lines of FORTRAN code) into object-oriented C++. Many important lessons have been learned during the past years; one of these is that the design must never be allowed to diverge from the code during maintenance and enhancement. Future work on open, integrated environments to support reengineering is being actively planned.

Pitman, C.↗