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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

The Database Query Support Processor (QSP)

The number and diversity of databases available to users continues to increase dramatically. Currently, the trend is towards decentralized, client server architectures that (on the surface) are less expensive to acquire, operate, and maintain than information architectures based on centralized, monolithic mainframes. The database query support processor (QSP) effort evaluates the performance of a network level, heterogeneous database access capability. Air Force Material Command's Rome Laboratory has developed an approach, based on ANSI standard X3.138 - 1988, 'The Information Resource Dictionary System (IRDS)' to seamless access to heterogeneous databases based on extensions to data dictionary technology. To successfully query a decentralized information system, users must know what data are available from which source, or have the knowledge and system privileges necessary to find out this information. Privacy and security considerations prohibit free and open access to every information system in every network. Even in completely open systems, time required to locate relevant data (in systems of any appreciable size) would be better spent analyzing the data, assuming the original question was not forgotten. Extensions to data dictionary technology have the potential to more fully automate the search and retrieval for relevant data in a decentralized environment. Substantial amounts of time and money could be saved by not having to teach users what data resides in which systems and how to access each of those systems. Information describing data and how to get it could be removed from the application and placed in a dedicated repository where it belongs. The result simplified applications that are less brittle and less expensive to build and maintain. Software technology providing the required functionality is off the shelf. The key difficulty is in defining the metadata required to support the process. The database query support processor effort will provide quantitative data on the amount of effort required to implement an extended data dictionary at the network level, add new systems, adapt to changing user needs, and provide sound estimates on operations and maintenance costs and savings.

Source record↗
NASA NTRS2004

Impregnation of Catalytic Metals in Single-Walled Carbon Nanotubes for Toxic Gas Conversion in Life Support System

Carbon nanotubes (CNTs) possess extraordinary properties such as high surface area, ordered chemical structure that allows functionalization, larger pore volume, and very narrow pore size distribution that have attracted considerable research attention from around the world since their discovery in 1991. The development and characterization of an original and innovative approach for the control and elimination of gaseous toxins using single walled carbon nanotubes (SWNTs) promise superior performance over conventional approaches due to the ability to direct the selective uptake of gaseous species based on their controlled pore size, increased adsorptive capacity due to their increased surface area and the effectiveness of carbon nanotubes as catalyst supports for gaseous conversion. We present our recent investigation of using SWNTs as catalytic supporting materials to impregnate metals, such as rhodium (Rh), palladium (Pd) and other catalysts. A protocol has been developed to oxidize the SWNTs first and then impregnate the Rh in aqueous rhodium chloride solution, according to unique surface properties of SWNTs. The Rh has been successfully impregnated in SWNTs. The Rh-SWNTs have been characterized by various techniques, such as TGA, XPS, TEM, and FTIR. The project is funded by a NASA Research Announcement Grant to find applications of single walled nanocarbons in eliminating toxic gas Contaminant in life support system. This knowledge will be utilized in the development of a prototype SWNT KO, gas purification system that would represent a significant step in the development of high efficiency systems capable of selectively removing specific gaseous for use in regenerative life support system for human exploration missions.

Li, Jing↗
NASA NTRS2006

A Bioinformatics Facility for NASA

Building on an existing prototype, we have fielded a facility with bioinformatics technologies that will help NASA meet its unique requirements for biological research. This facility consists of a cluster of computers capable of performing computationally intensive tasks, software tools, databases and knowledge management systems. Novel computational technologies for analyzing and integrating new biological data and already existing knowledge have been developed. With continued development and support, the facility will fulfill strategic NASA s bioinformatics needs in astrobiology and space exploration. . As a demonstration of these capabilities, we will present a detailed analysis of how spaceflight factors impact gene expression in the liver and kidney for mice flown aboard shuttle flight STS-108. We have found that many genes involved in signal transduction, cell cycle, and development respond to changes in microgravity, but that most metabolic pathways appear unchanged.

Schweighofer, Karl↗
NASA NTRS2008

The Power of Story

A major knowledge-sharing issue that is the source of many project problems: how to communicate our intentions so that the information received is the same as the information given. One answer is conversation-the back-and-forth of statement, question, and response that gradually brings talkers and listeners to a shared understanding. Stories also offer a way to share knowledge effectively. While the story teller's intent and the listener's interpretation will not be identical, a good story reliably communicates essential knowledge so it is not only understood but absorbed and embraced. Narrative is one of the oldest knowledge-transfer systems in the world. Religion knows it. Politicians know it. Fairytales know it. Now, knowledge management practitioners are coming to know it, too. But why are stories such a powerful knowledge-transfer tool? And what kinds of knowledge do they transfer? Joseph Campbell, the mythologist, defined stories as serving four major functions: the mystical, the cosmological, the sociological, and the pedagogical. The mystical function of narrative lies in its ability to open up emotional realization that often connects with a transcendent idea such as love or forgiveness. He calls this realization "mystical" because it connects the self with the universal. What Campbell calls the cosmological function of stories relates the self to the outside world, focusing on action, on understanding cause and effect and our role in it. For the cosmological function of stories "to be up to date and really to work in the minds of people who are living in the modern scientific world," Campbell notes, "it must incorporate the modern scientific world." We must continually tell stories that demonstrate our current vision of the world. The sociological function of stories, Campbell explains, helps maintain and validate the social order of a society. Stories pass on information about power relationships, taboos, laws, and the inner workings of communities. Countries and religions have stories that serve this function and so do organizations and project teams, where stories about project work communicate information about behaviors and attitudes that are expected and rewarded or frowned upon and penalized. Functioning pedagogically, says Campbell, narratives guide individuals harmoniously through the stages of life in terms of their world today, with its current goods, values, and dangers. These are stories that deal with life transitions and guide us from one stage to another. Stories powerfully serve these functions partly because of two great strengths: their ability to engage listeners personally and emotionally and their use of metaphor. And it turns out that these two things are related.

Cohen, Don↗
NASA NTRS2016

Enhancing Systems Engineering Education Through Case Study Writing

Developing and refining methods for teaching systems engineering is part of Systems Engineering grand challenges and agenda for research in the SE research community. Retention of systems engineering knowledge is a growing concern in the United States as the baby boom generation continues to retire and the faster pace of technology development does not allow for younger generations to gain experiential knowledge through years of practice. Government agencies, including the National Aeronautics and Space Administration (NASA), develop their own curricula and SE leadership development programs to "grow their own" systems engineers. Marshall Space Flight Center (MSFC) conducts its own Center-focused Marshall Systems Engineering Leadership Development Program (MSELDP), a competitive program consisting of coursework, a guest lecture series, and a rotational assignment into an unfamiliar organization engaged in systems engineering. Independently, MSFC developed two courses to address knowledge retention and sharing concerns: Real World Marshall Mission Success course and its Case Study Writers Workshop and Writers Experience. Teaching case study writing and leading students through a hands-on experience at writing a case study on an SE topic can enhance SE training and has the potential to accelerate the transfer of experiential knowledge. This paper is an overview of the pilot experiences with teaching case study writing, its application in case study-based learning, and identifies potential areas of research and application for case study writing in systems engineering education.

Stevens, Jennifer Stenger↗
NASA NTRS1988

SPECTRUM - A system for the analysis of imaging spectrometer data

This paper examines several design issues related to the development of SPECTRUM, a knowledge-based system for the geological interpretation of imaging spectrometer data. SPECTRUM is implemented using a combination of the programming languages STAR and C, which are coupled both at the level of procedures - involving function calls between the two languages - and at the level of data structures - involving the formation of a hybrid knowledge base shared by the two languages. Aspects of the coupling relating to each level of the implementation are described, followed by a listing of general observations regarding the coupling of symbolic and numerical techniques as extracted from the SPECTRUM project.

Borchardt, Gary C.↗
NASA NTRS1993

A knowledge engineering taxonomy for intelligent tutoring system development

This paper describes a study addressing the issue of developing an appropriate mapping of knowledge acquisition methods to problem types for intelligent tutoring system development. Recent research has recognized that knowledge acquisition methodologies are not general across problem domains; the effectiveness of a method for obtaining knowledge depends on the characteristics of the domain and problem solving task. Southwest Research Institute developed a taxonomy of problem types by evaluating the characteristics that discriminate between problems and grouping problems that share critical characteristics. Along with the problem taxonomy, heuristics that guide the knowledge acquisition process based on the characteristics of the class are provided.

Fink, Pamela K.↗
NASA NTRSDate not supplied

Uncovering Hazards Using a Multi-Objective Optimization to Explore the Faulty State-Space

Considering resilience when designing complex engineered systems is crucial to ensure the system is safe under unexpected hazardous scenarios. Traditional risk-based approaches, such as Failure Modes and Effects Analysis (FMEA) are useful for designing the system to mitigate hazardous scenarios that can be identified by the designer, but often require experience or prior knowledge of system failures to generate. More recently, researchers have developed simulation tools that enable the designer to model large sets of hazardous scenarios (driven by both internal faults and external factors) through simulation. While these tools enable a wider scope of fault modes to be evaluated (e.g., by injecting combined set of fault modes or injecting modes at different times), the resulting assessments (like FMEA) still require knowledge of the specific modes to be evaluated. However, failure to analyze a wide variety of fault scenarios can lead to an incomplete picture of the system resilience, especially to "surprise events'' which may be difficult for the designer to identify and predict beforehand. To overcome this challenge, previous work developed a fault sampling approach for resilience simulations which would procedurally-generate a wide variety of potential faults by systematically perturbing the health states of the system. While the resulting fault modes generated covered a much larger space hazards than would be otherwise considered (and identified many unique failure trajectories which would not have otherwise been identified), it also significantly increased the computational cost of the analysis and resulted in the simulation and analysis of a large set of essentially duplicate scenarios. Additionally, as the number of dimensions in the faulty state-space increases, the full elaboration of possible modes becomes computationally infeasible, justifying the use of a more targeted search. To resolve this limitation, this work proposes the use of a multiobjective optimization algorithm to search the health state space for potential fault modes that are both (1) hazardous and (2) unique. To solve this type of problem, this work proposes the use of a cooperative co-evolutionary algorithm. To demonstrate this approach, it will be applied to a model of an autonomous rover which uses line markings to navigate, focusing on potential hazards in the drive system which could cause the rover to crash. To determine the merit of the approach, it will further be compared with the previously-presented range elaboration approach and a random mode generation approach on the basis of computational efficiency and found modes.

Resilience↗
NASA NTRS1992

Situation Management in the Link Monitor and Control Operator Assistant (LMCOA)

This paper describes a knowledge-based system called the Situation Manager that was developed for the Link Monitor and Control Operator Assistant (LMCOA) at the Jet Propulsion Laboratory. This system was developed in response to a number of deficiencies that were identified in an earlier version of the LMCOA: (1) the need to close the control loop between sending a directive and knowing when its execution is complete (versus just closing the communications loop), (2) the need to recognize an anomaly and alert the operator when a directive is rejected or a link device fails, and (3) the need to suggest ways to work around an anomaly, provided that it is recognizable. In response to these needs, the Situation Manager has been designed to provide the LMCOA with three basic capabilities: situation assessment, anomaly diagnosis, and recovery from commonly

Monitor↗
NASA NTRS1987

Microprocessor control and networking for the amps breadboard

Future space missions will require more sophisticated power systems, implying higher costs and more extensive crew and ground support involvement. To decrease this human involvement, as well as to protect and most efficiently utilize this important resource, NASA has undertaken major efforts to promote progress in the design and development of autonomously managed power systems. Two areas being actively pursued are autonomous power system (APS) breadboards and knowledge-based expert system (KBES) applications. The former are viewed as a requirement for the timely development of the latter. Not only will they serve as final testbeds for the various KBES applications, but will play a major role in the knowledge engineering phase of their development. The current power system breadboard designs are of a distributed microprocessor nature. The distributed nature, plus the need to connect various external computer capabilities (i.e., conventional host computers and symbolic processors), places major emphasis on effective networking. The communications and networking technologies for the first power system breadboard/test facility are described.

Floyd, Stephen A.↗
NASA NTRS1987

Artificial intelligence and space power systems automation

Various applications of artificial intelligence to space electrical power systems are discussed. An overview is given of completed, on-going, and planned knowledge-based system activities. These applications include the Nickel-Cadmium Battery Expert System (NICBES) (the expert system interfaced with the Hubble Space Telescope electrical power system test bed); the early work with the Space Station Experiment Scheduler (SSES); the three expert systems under development in the space station advanced development effort in the core module power management and distribution system test bed; planned cooperation of expert systems in the Core Module Power Management and Distribution (CM/PMAD) system breadboard with expert systems for the space station at other research centers; and the intelligent data reduction expert system under development.

Weeks, David J.↗
NASA NTRS1994

Temperature measurement using infrared imaging systems during turbine engine altitude testing

This report details the use of infrared imaging for temperature measurement and thermal pattern determination during simulated altitude engine testing in the NASA Lewis Propulsion Systems Laboratory. Three identical argon-cooled imaging systems were installed in the facility exhaust collector behind sapphire windows to look at engine internal surfaces. The report describes the components of each system, presents the specifics of the complicated installation, and explains the operation of the systems during engine testing. During the program, several problems emerged, such as argon contamination system, component overheating, cracked sapphire windows, and other unexplained effects. This report includes a summary of the difficulties as well as the solutions developed. The systems performed well, considering they were in an unusually harsh exhaust environment. Both video and digital data were recorded, and the information provided valuable material for the engineers and designers to quickly make any necessary design changes to the engine hardware cooling system. The knowledge and experience gained during this program greatly simplified the installation and use of the systems during later test programs in the facility. The infrared imaging systems have significantly enhanced the measurement capabilities of the facility, and have become an outstanding and versatile testing resource in the Propulsion Systems Laboratory.

Burns, Maureen E.↗
NASA NTRS2016

Spacecraft Fire Safety Research at NASA Glenn Research Center

Appropriate design of fire detection systems requires knowledge of both the expected fire signature and the background aerosol levels. Terrestrial fire detection systems have been developed based on extensive study of terrestrial fires. Unfortunately there is no corresponding data set for spacecraft fires and consequently the fire detectors in current spacecraft were developed based upon terrestrial designs. In low gravity, buoyant flow is negligible which causes particles to concentrate at the smoke source, increasing their residence time, and increasing the transport time to smoke detectors. Microgravity fires have significantly different structure than those in 1-g which can change the formation history of the smoke particles. Finally the materials used in spacecraft are different from typical terrestrial environments where smoke properties have been evaluated. It is critically important to detect a fire in its early phase before a flame is established, given the fixed volume of air on any spacecraft. Consequently, the primary target for spacecraft fire detection is pyrolysis products rather than soot. Experimental investigations have been performed at three different NASA facilities which characterize smoke aerosols from overheating common spacecraft materials. The earliest effort consists of aerosol measurements in low gravity, called the Smoke Aerosol Measurement Experiment (SAME), and subsequent ground-based testing of SAME smoke in 55-gallon drums with an aerosol reference instrument. Another set of experiments were performed at NASAs Johnson Space Center White Sands Test Facility (WSTF), with additional fuels and an alternate smoke production method. Measurements of these smoke products include mass and number concentration, and a thermal precipitator was designed for this investigation to capture particles for microscopic analysis. The final experiments presented are from NASAs Gases and Aerosols from Smoldering Polymers (GASP) Laboratory, with selected results focusing on realistic fuel preparations and heating profiles with regards to early detection of smoke. SAFFIRE is the upcoming large-scale fire experiment which will be executed in a Cygnus vehicle after it undocks from the ISS.

Aerosol↗
NASA NTRS1985

Expert systems and their use in augmenting design optimization

The challenging requirements that are evolving for future aircraft demand that each design be optimally integrated, for the penalties imposed by nonoptimal performance are significant. Classic numerical optimization algorithms have been and will continue to be important tools for aircraft designers. These methods are, however, limited to certain categories of aircraft design variables, leaving the remainder to be determined by the user. A method that makes use of knowledge-based expert systems offers the potential for aiding the conceptual design process in a way that is similar to that of numerical optimization, except that it would address discrete, discontinuous, abstract, or any other unoptimized aspect of vehicle design and integration. Other unique capabilities such as automatic discovery and learning in design may also be achievable in the near term. This paper discusses current practice in conceptual aircraft design and knowledge-based systems, and how knowledge-based systems can be used in conceptual design.

Kidwell, G. H.↗
NASA NTRS1980

Field size, length, and width distributions based on LACIE ground truth data

The development of agricultural remote sensing systems requires knowledge of agricultural field size distributions so that the sensors, sampling frames, image interpretation schemes, registration systems, and classification systems can be properly designed. Malila et al. (1976) studied the field size distribution for wheat and all other crops in two Kansas LACIE (Large Area Crop Inventory Experiment) intensive test sites using ground observations of the crops and measurements of their field areas based on current year rectified aerial photomaps. The field area and size distributions reported in the present investigation are derived from a representative subset of a stratified random sample of LACIE sample segments. In contrast to previous work, the obtained results indicate that most field-size distributions are not log-normally distributed. The most common field size observed in this study was 10 acres for most crops studied.

Pitts, D. E.↗
NASA NTRS1984

The Saturn system

An overview is presented of the results of recent studies of the Saturn system. Present knowledge of the planet, the magnetosphere, the rings, the satellites, and the origin of the Saturn system is summarized.

Stone, E. C.↗
NASA NTRS1987

Space power system automation approaches at the George C. Marshall Space Flight Center

This paper discusses the automation approaches employed in various electrical power system breadboards at the Marshall Space Flight Center. Of particular interest is the application of knowledge-based systems to fault management and dynamic payload scheduling. A description of each major breadboard and the automation approach taken for each is given.

Weeks, D. J.↗