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At least 55 records · Page 3

Use of an expert system data analysis manager for space shuttle main engine test evaluation

The ability to articulate, collect, and automate the application of the expertise needed for the analysis of space shuttle main engine (SSME) test data would be of great benefit to NASA liquid rocket engine experts. This paper describes a project whose goal is to build a rule-based expert system which incorporates such expertise. Experiential expertise, collected directly from the experts currently involved in SSME data analysis, is used to build a rule base to identify engine anomalies similar to those analyzed previously. Additionally, an alternate method of expertise capture is being explored. This method would generate rules inductively based on calculations made using a theoretical model of the SSME's operation. The latter rules would be capable of diagnosing anomalies which may not have appeared before, but whose effects can be predicted by the theoretical model.

Abernethy, Ken↗

Advanced Air Bag Technology Assessment

As a result of the concern for the growing number of air-bag-induced injuries and fatalities, the administrators of the National Highway Traffic Safety Administration (NHTSA) and the National Aeronautics and Space Administration (NASA) agreed to a cooperative effort that "leverages NHTSA's expertise in motor vehicle safety restraint systems and biomechanics with NASAs position as one of the leaders in advanced technology development... to enable the state of air bag safety technology to advance at a faster pace..." They signed a NASA/NHTSA memorandum of understanding for NASA to "evaluate air bag to assess advanced air bag performance, establish the technological potential for improved technology (smart) air bag systems, and identify key expertise and technology within the agency (i.e., NASA) that can potentially contribute significantly to the improved effectiveness of air bags." NASA is committed to contributing to NHTSAs effort to: (1) understand and define critical parameters affecting air bag performance; (2) systematically assess air bag technology state of the art and its future potential; and (3) identify new concepts for air bag systems. The Jet Propulsion Laboratory (JPL) was selected by NASA to respond to the memorandum of understanding by conducting an advanced air bag technology assessment. JPL analyzed the nature of the need for occupant restraint, how air bags operate alone and with safety belts to provide restraint, and the potential hazards introduced by the technology. This analysis yielded a set of critical parameters for restraint systems. The researchers examined data on the performance of current air bag technology, and searched for and assessed how new technologies could reduce the hazards introduced by air bags while providing the restraint protection that is their primary purpose. The critical parameters which were derived are: (1) the crash severity; (2) the use of seat belts; (3) the physical characteristics of the occupants; (4) the proximity of the occupants to the airbag module; (5) the deployment time, which includes the time to sense the need for deployment, the inflator response parameters, the air bag response, and the reliability of the air bag. The requirements for an advanced air bag technology is discussed. These requirements includes that the system use information related to: (1) the crash severity; (2) the status of belt usage; (3) the occupant category; and (4) the proximity to the air bag to adjust air bag deployment. The parameters for the response of the air bag are: (1) deployment time; (2) inflator parameters; and (3) air bag response and reliability. The state of occupant protection advanced technology is reviewed. This review includes: the current safety restraint systems, and advanced technology characteristics. These characteristics are summarized in a table, which has information regarding the technology item, the potential, and an date of expected utilization. The use of technology and expertise at NASA centers is discussed. NASA expertise relating to sensors, computing, simulation, propellants, propulsion, inflatable systems, systems analysis and engineering is considered most useful. Specific NASA technology developments, which were included in the study are: (1) a capacitive detector; (2) stereoscopic vision system; (3) improved crash sensors; (4) the use of the acoustic signature of the crash to determine crash severity; and (5) the use of radar antenna for pre-crash sensing. Information relating to injury risk assessment is included, as is a summary of the areas of the technology which requires further development.

Phen, R. L.↗

Derivation of Capabilities and Resources for Treating Medical Conditions in Deep Space

BACKGROUND: Medical care in spaceflight requires the adaptation of terrestrial standards to the constraints of the space environment. However, there is often conflict between the ideal resources required for treatment and diagnosis of a medical condition, and the constraints on their mass, volume, data needs, etc. This optimization of trades between medical risk and resources will be a significant challenge for deep space medical system design. METHODS: A team of physicians with a broad range of expertise reviewed the 120 medical conditions on the condition list for NASA’s Informing Mission Planning via analysis of Complex Tradespaces Medical Database (IMPACT-MD). Each team member was assigned a subset of conditions based on their experience and training. The assigned physician generated a proposed list of capabilities, definitions, and resources required to treat each condition based on terrestrial practice guidelines, medical literature, and subject matter expertise. Additional specialists were consulted for conditions where expertise was not present within the main group. The proposed list was then reviewed by the broader team and modified as needed to achieve consensus. Each capability and resource was then assigned parameters to define quantity required per medical event, necessity, training level required, and primacy order of any alternative resources. These capabilities and resources were placed into condition specific tables and delivered to a team of engineers who added mass and volume data for each specific resource and converted the table into a database for use as input to a computational model to simulate spaceflight (IMPACT) DISCUSSION: This process ensures that a minimum of three subject matter experts review and agree upon the scope of practice, medical diagnostic tools, and treatment modalities that would be necessary to address emergent and non-emergent conditions that may arise during spaceflight to inform requirements during the vehicle design phase. The method is scalable to any design reference mission and permits modification of the existing database as information, conditions or experience are added. By including specialists, generalists, and those with subject matter expertise in the spaceflight environment on the team, we ensure that the included capabilities represent a realistic and actionable foundation for planning deep space missions.

D R Levin↗

Marin County Wildfires Ii: Improving Fire Suppression Modeling to Inform Fire Prevention and Suppression Decisions in Marin County, Ca

A future of increased wildfires requires greater integration of spatial analysis and local knowledge of emergency responders. We examine the application of a Potential Operational Delineations (PODs) framework for strategic pre-fire planning in Marin County. PODs are spatial units for wildfire management that combine predictive modeling and local firefighter expertise to identify potential control locations as unit boundaries and assess the difficulty of suppression within units. Additionally, this project explores the integration of road networks and social vulnerability to assess environmental justice in evacuation safety. This project constitutes a novel application of the PODs framework as it integrates expertise from Marin County senior firefighters with a Fireline Location Model (FLM) to achieve POD definition and uses a Suppression Difficulty Score (SDS) to rank each POD. The FLM uses network analysis and hydrologic modeling to identify key roads and ridgelines as boundaries and combines them with expert knowledge, in the form of workshops, to construct PODs. Once identified, PODs are classified using SDS, which includes processed inputs such as LiDAR-derived aboveground biomass, ECOSTRESS Evaporative Stress Index, land use cover type from Sentinel-2 Imagery, and a digital elevation model. Environmental justice for evacuation safety incorporated three key road metrics such as connectivity, travel area, and exit capacity, the Social Vulnerability Index from the Center for Disease Control, and cell coverage to determine a final Evacuation Difficulty Score. Results indicate a strong link between road networks as primary POD boundaries, with ridgelines and waterways as secondary and tertiary locations. Specifically, we find 78.5% of expertise-identified POD boundaries align with FLM-determined boundaries. More validation is needed to support this process; however, initial results signal a feasible framework to integrate expertise and spatial analysis in local level strategic fire planning

Wildfire modeling↗

Humans to Mars, but How Many? Using Training Requirements Modeling to Inform Crew Size

Missions to Mars will differ from previous human spaceflight missions in that the onboard crew of astronauts will be required to operate in an Earth-independent manner due to the long communication delays. Without a systematic, repeatable process to determine the number and composition of crew necessary to successfully accomplish these missions, NASA increases the risk that crew sizes may be too small to meet primary mission objectives under nominal conditions and, more consequentially, that crewmembers may not have the expertise needed to successfully respond to unforeseen failures without the real-time expertise of the Mission Control Central (MCC) team NASA currently relies upon. The NASA Engineering and Safety Center (NESC) is developing a methodology for assessing the trade space of factors that affect the number of crew for future missions. This methodology includes the consideration of results from three human performance models developed using the Improved Performance Research and Integration Tool (IMPRINT) modeling platform as well as a custom-built model on expertise trained within the crew. The IMPRINT results will be presented in the modeling and simulation sub-tag. Here we present results of a model based on NASA’s crew qualification and responsibility matrix (CQRM), a tool used to identify the crew qualifications for each area of responsibility (operation, system, and payload) for a mission. The model outputs an optimized allocation of training assignments along with a flight-assigned CQRM that can be used to consider the expertise that can be trained within a crew of a given size. We discuss the CQRM model result implications on the trade space for Mars mission crew size.

Mars↗

Humans to Mars, but How Many? Using Imprint Human Performance Models to Inform Crew Size

HUMANS TO MARS, BUT HOW MANY? USING IMPRINT HUMAN PERFORMANCE MODELS TO INFORM CREW SIZE Missions to Mars will differ from previous human spaceflight missions in that the onboard crew of astronauts will be required to operate in an Earth-independent manner due to long communication delays. Without a systematic, repeatable process to determine the number and composition of crew necessary to successfully accomplish these missions, NASA increases the risk that crew sizes may be too small to meet primary mission objectives under nominal conditions and, more consequentially, that crewmembers may not have the expertise needed to successfully respond to unforeseen failures without the real-time expertise of the Mission Control Central (MCC) team NASA currently relies upon. The NASA Engineering and Safety Center (NESC) is developing a methodology for assessing the trade space of factors that affect the number of crew for future missions. This methodology includes the consideration of results from three human performance models developed using the Improved Performance Research and Integration Tool (IMPRINT) modeling platform as well as a custom-built model on expertise trained within the crew. The custom-built crew expertise model results will be presented in the training sub-tag. Here we present results of the three IMPRINT models. Two of these models were built using IMPRINT’s Operations Model capability, with detailed task networks for specific systems and scenarios allowing for a comprehensive mental workload analysis on certain crew positions. The third model was built using IMPRINT’s Force Model capability, allowing for a higher-level manpower analysis based on crew engagement in activities performed over a longer Mars transit scenario, and how those activities may be impacted by unplanned events and new tasking unique to the Mars mission. Differences between the models will be presented, as well as examples of model results and a discussion of how those results may inform future Mars mission manpower requirements, system design, and operating procedures.

Donna L Dempsey↗

Humans to Mars, but How Many? Using Training Requirements Modeling to Inform Crew Size

Missions to Mars will differ from previous human spaceflight missions in that the onboard crew of astronauts will be required to operate in an Earth-independent manner due to the long communication delays. Without a systematic, repeatable process to determine the number and composition of crew necessary to successfully accomplish these missions, NASA increases the risk that crew sizes may be too small to meet primary mission objectives under nominal conditions and, more consequentially, that crewmembers may not have the expertise needed to successfully respond to unforeseen failures without the real-time expertise of the Mission Control Central (MCC) team NASA currently relies upon. The NASA Engineering and Safety Center (NESC) is developing a methodology for assessing the trade space of factors that affect the number of crew for future missions. This methodology includes the consideration of results from three human performance models developed using the Improved Performance Research and Integration Tool (IMPRINT) modeling platform as well as a custom-built model on expertise trained within the crew. The IMPRINT results will be presented in the modeling and simulation sub-tag. Here we present results of a model based on NASA’s crew qualification and responsibility matrix (CQRM), a tool used to identify the crew qualifications for each area of responsibility (operation, system, and payload) for a mission. The model outputs an optimized allocation of training assignments along with a flight-assigned CQRM that can be used to consider the expertise that can be trained within a crew of a given size. We discuss the CQRM model result implications on the trade space for Mars mission crew size.

Mars↗

Humans to Mars, but How Many? Trade Space Analyses for Mars Mission Crew Size

Missions to Mars will differ from previous human spaceflight missions in that the crew of astronauts will be required to operate in an Earth-independent manner due to the long communication delays. Without a systematic, repeatable process to determine the number and composition of crew necessary to successfully accomplish these missions, NASA increases the risk that crew sizes may be too small to meet primary mission objectives under nominal conditions and, more consequentially, that crewmembers may not have the expertise needed to successfully respond to unforeseen failures without the real-time expertise of the Mission Control Central (MCC) team NASA currently relies upon. The NASA Engineering and Safety Center (NESC) developed a methodology for assessing the trade space of factors that affect the number of crew for Mars missions based on human performance and expertise modeling. This methodology includes the consideration of results from three human performance models developed using the Improved Performance Research and Integration Tool (IMPRINT) modeling platform as well as a custom-built model on expertise trained within the crew based on NASA’s crew qualification and responsibilities matrix (CQRM). We present example model results and discuss implications on trade space analyses for Mars mission crew size.

Mars Mission↗

Evaluating software testing strategies

The strategies of code reading, functional testing, and structural testing are compared in three aspects of software testing: fault detection effectiveness, fault detection cost, and classes of faults detected. The major results are the following: (1) Code readers detected more faults than did those using the other techniques, while functional tester detected more faults than did structural testers; (2) Code readers had a higher fault detection rate than did those using the other methods, while there was no difference between functional testers and structural testers; (3) Subjects testing the abstract data type detected the most faults and had the highest fault detection rate, while individuals testing the database maintainer found the fewest faults and spent the most effort testing; (4) Subjects of intermediate and junior expertise were not different in number or percentage of faults found, fault detection rate, or fault detection effort; (5) subjects of advanced expertise found a greater number of faults than did the others, found a greater percentage of faults than did just those of junior expertise, and were not different from the others in either fault detection rate or effort; and (6) Code readers and functional testers both detected more omission faults and more control faults than did structural testers, while code readers detected more interface faults than did those using the other methods.

Selby, R. W., Jr.↗

Independent verification and validation for Space Shuttle flight software

The Committee for Review of Oversight Mechanisms for Space Shuttle Software was asked by the National Aeronautics and Space Administration's (NASA) Office of Space Flight to determine the need to continue independent verification and validation (IV&V) for Space Shuttle flight software. The Committee found that the current IV&V process is necessary to maintain NASA's stringent safety and quality requirements for man-rated vehicles. Therefore, the Committee does not support NASA's plan to eliminate funding for the IV&V effort in fiscal year 1993. The Committee believes that the Space Shuttle software development process is not adequate without IV&V and that elimination of IV&V as currently practiced will adversely affect the overall quality and safety of the software, both now and in the future. Furthermore, the Committee was told that no organization within NASA has the expertise or the manpower to replace the current IV&V function in a timely fashion, nor will building this expertise elsewhere necessarily reduce cost. Thus, the Committee does not recommend moving IV&V functions to other organizations within NASA unless the current IV&V is maintained for as long as it takes to build comparable expertise in the replacing organization.

Source record↗

Modeling software systems by domains

The Software Architectures Engineering (SAE) Project at the Software Engineering Institute (SEI) has developed engineering modeling techniques that both reduce the complexity of software for domain-specific computer systems and result in systems that are easier to build and maintain. These techniques allow maximum freedom for system developers to apply their domain expertise to software. We have applied these techniques to several types of applications, including training simulators operating in real time, engineering simulators operating in non-real time, and real-time embedded computer systems. Our modeling techniques result in software that mirrors both the complexity of the application and the domain knowledge requirements. We submit that the proper measure of software complexity reflects neither the number of software component units nor the code count, but the locus of and amount of domain knowledge. As a result of using these techniques, domain knowledge is isolated by fields of engineering expertise and removed from the concern of the software engineer. In this paper, we will describe kinds of domain expertise, describe engineering by domains, and provide relevant examples of software developed for simulator applications using the techniques.

Dippolito, Richard↗

Advanced automation of a prototypic thermal control system for Space Station

Viewgraphs on an advanced automation of a prototypic thermal control system for space station are presented. The Thermal Expert System (TEXSYS) was initiated in 1986 as a cooperative project between ARC and JCS as a way to leverage on-going work at both centers. JSC contributed Thermal Control System (TCS) hardware and control software, TCS operational expertise, and integration expertise. ARC contributed expert system and display expertise. The first years of the project were dedicated to parallel development of expert system tools, displays, interface software, and TCS technology and procedures by a total of four organizations.

Dominick, Jeff↗

Deep near-infrared survey of the Southern Sky (DENIS)

DENIS (Deep Near-Infrared Survey of the Southern Sky) will be the first complete census of astronomical sources in the near-infrared spectral range. The challenges of this novel survey are both scientific and technical. Phenomena radiating in the near-infrared range from brown dwarfs to galaxies in the early stages of cosmological evolution, the scientific exploitation of data relevant over such a wide range requires pooling expertise from several of the leading European astronomical centers. The technical challenges of a project which will provide an order of magnitude more sources than given by the IRAS space mission, and which will involve advanced data-handling and image-processing techniques, likewise require pooling of hardware and software resources, as well as of human expertise. The DENIS project team is composed of some 40 scientists, computer specialists, and engineers located in 5 European Community countries (France, Germany, Italy, The Netherlands, and Spain), with important contributions from specialists in Australia, Brazil, Chile, and Hungary. DENIS will survey the entire southern sky in 3 colors, namely in the I band at a wavelength of 0.8 micron, in the 1.25 micron J band, and in the 2.15 micron K' band. The sensitivity limits will be 18th magnitude in the I band, 16th in the J band, and 14.5th in the K' band. The angular resolution achieved will be 1 arcsecond in the I band, and 3.0 arcseconds in the J and K' bands. The European Southern Observatory 1 m telescope on La Silla will be dedicated to survey use during operations expected to last four years, commencing in late 1993. DENIS aims to provide the astronomical community with complete digitized infrared images of the full southern sky and a catalogue of extracted objects, both of the best quality and in readily accessible form. This will be achieved through dedicated software packages and specialized catalogues, and with assistance from the Leiden and Paris Data Analysis Centers. The data will be mailed on DAT tapes from La Silla to the two Data Analysis Centers for further processing. Two centers are necessary because of the shear quantity of data and because of the complementary roles the Centers will develop, each exploiting its own particular expertise. The Leiden Data Analysis Center (LDAC) will extract objects, establish their parameters, and archive them into a source catalogue. The LDAC will collaborate with the Groningen Space Research group that has gained experience in infrared image handling from the IRAS satellite. The Paris Data Analysis Center (PDAC) will be responsible for archiving and preprocessing the raw data to provide a homogeneous set of data suitable for further reduction in both the Leiden and Paris data analysis streams. The PDAC will also extract and archive images for the sources flagged by the LDAC as extended, and create a catalogue of galaxies. In exploiting the DENIS data we foresee the collaboration with other data analysis centers, such as the Observatoire de Lyon where the relevant DENIS catalogue of galaxies can be incorporated into their extragalactic database. The Point Sources and the Small Extended Sources catalogues could be incorporated in the Late Type Star database at Montpellier, and in the SIMBAD database as CDS. At Groningen the IRAS Point Source catalogue and/or image data can be merged with the DENIS catalogues. At Meudon algorithms and software will be developed with main goal assessing the limits reachable for the homogeneity and intrinsic consistency between the ensemble of the images in the data base (flat-fielding, relative positioning of the fields, bootstrapped flux calibration) but also for the data analysis.

Deul, E.↗

Third CLIPS Conference Proceedings, volume 1

Expert systems are computed programs which emulate human expertise in well defined problem domains. The potential payoff from expert systems is high: valuable expertise can be captured and preserved, repetitive and/or mundane tasks requiring human expertise can be automated, and uniformity can be applied in decision making processes. The C Language Integrated Production Systems (CLIPS) is an expert system building tool, developed at the Johnson Space Center, which provides a complete environment for the development and delivery of rule and/or object based expert systems. CLIPS was specifically designed to provide a low cost option for developing and deploying expert system applications across a wide range of hardware platforms. The development of CLIPS has helped to improve the ability to deliver expert systems technology throughout the public and private sectors for a wide range of applications and diverse computing environments.

Riley, Gary↗

CLIPS: The C language integrated production system

Expert systems are computer programs which emulate human expertise in well defined problem domains. The potential payoff from expert systems is high: valuable expertise can be captured and preserved, repetitive and/or mundane tasks requiring human expertise can be automated, and uniformity can be applied in decision making processes. The C Language Integrated Production System (CLIPS) is an expert system building tool, developed at the Johnson Space Center, which provides a complete environment for the development and delivery of rule and/or object based expert systems. CLIPS was specifically designed to provide a low cost option for developing and deploying expert system applications across a wide range of hardware platforms. The commercial potential of CLIPS is vast. Currently, CLIPS is being used by over 5,000 individuals throughout the public and private sector. Because the CLIPS source code is readily available, numerous groups have used CLIPS as the basis for their own expert system tools. To date, three commercially available tools have been derived from CLIPS. In general, the development of CLIPS has helped to improve the ability to deliver expert system technology throughout the public and private sectors for a wide range of applications and diverse computing environments.

Riley, Gary↗

Report on Cosmic Dust Capture Research and Development for the Exobiology Program

Collaboration with Ames' personnel was in: 1) grant administration, 2) intellectual science support, 3) collaboration with the University of Paris for the Mir flight experiment, and 4) arranging scanning and X-ray probe analytical support from UCB and SUNYP. LNIMS provided access to: 1) analytical research instruments, 2) chemical analyses support, 3) cleanroom facilities, and 4) design and fabrication expertise of hardware and electronics. They also supported the hypervelocity testing along with test data acquisition and its reduction for the breadboard instrument. A&M Associates provided technical expertise and support on determining the expected charges on orbital particles and a conceptual design for a breadboard particle charge detection sensor. University of California provided analytical support for the recovered Mir flight modules using their unique scanning capability to detect particle tracks in the aerogel. SUNYP, along with help from the University of Chicago, analyzed particle tracks found in the aerogel for biogenic compounds using an x-ray probe instrument. Dr. Schultz provided access to his experiments and the benefits of his considerable hyper-velocity testing expertise at the Ames hypervelocity gun facility, and this proved beneficial to our development testing, significantly reducing the test time and cost for the breadboard instrument development testing. The participants in this activity acknowledge and thank the National Aeronautics and Space Administration and its Ames Research Center for providing the necessary support and resources to conduct this investigation on instrument technology for exobiology application and being able to acquire some interesting results. Primarily, the newly identified technology problems for future research are the important results of this research.

Nishioka, Kenji↗

Hosted Services for Advanced V and V Technologies: An Approach to Achieving Adoption without the Woes of Usage

Attempts to achieve widespread use of software verification tools have been notably unsuccessful. Even 'straightforward', classic, and potentially effective verification tools such as lint-like tools face limits on their acceptance. These limits are imposed by the expertise required applying the tools and interpreting the results, the high false positive rate of many verification tools, and the need to integrate the tools into development environments. The barriers are even greater for more complex advanced technologies such as model checking. Web-hosted services for advanced verification technologies may mitigate these problems by centralizing tool expertise. The possible benefits of this approach include eliminating the need for software developer expertise in tool application and results filtering, and improving integration with other development tools.

Koga, Dennis↗