5,505 research outputs found

    Determination of lunar ilmenite abundances from remotely sensed data

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    The mineral ilmenite (FeTiO3) was found in abundance in lunar mare soils returned during the Apollo project. Lunar ilmenite often contains greater than 50 weight-percent titanium dioxide (TiO2), and is a primary potential resource for oxygen and other raw materials to supply future lunar bases. Chemical and spectroscopic analysis of the returned lunar soils produced an empirical function that relates the spectral reflectance ratio at 400 and 560 nm to the weight percent abundance of TiO2. This allowed mapping of the lunar TiO2 distribution using telescopic vidicon multispectral imaging from the ground; however, the time variant photometric response of the vidicon detectors produced abundance uncertainties of at least 2 to 5 percent. Since that time, solid-state charge-coupled device (CCD) detector technology capable of much improved photometric response has become available. An investigation of the lunar TiO2 distribution was carried out utilizing groundbased telescopic CCD multispectral imagery and spectroscopy. The work was approached in phases to develop optimum technique based upon initial results. The goal is to achieve the best possible TiO2 abundance maps from the ground as a precursor to lunar orbiter and robotic sample return missions, and to produce a better idea of the peak abundances of TiO2 for benefaction studies. These phases and the results are summarized

    A nonparametric test for industrial specialization

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    We introduce a nonparametric microdata based test for industrial specialization and apply it to a single urban area. Our test employs establishment densities for specific industries, a population counterfactual, and a new correction for múltiple hypothesis testing to determine the statistical significance of specialization across both places and industries. Results highlight patterns of specialization which are extremely varied, with downtown places specializing in a number of service sector industries, while more suburban places specialize in both manufacturing and service industries. Business service industries are subject to more specialization than non-business service industries while the manufacturing sector contains the lowest representation of industries with specialized places. Finally, we compare the results of our test for specialization with recent tests of localization and show how these two classes of measures highlight the presence of both industry as well as place specific agglomerative forces

    Implementation of a Goal-Based Systems Engineering Process Using the Systems Modeling Language (SysML)

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    This paper describes the core framework used to implement a Goal-Function Tree (GFT) based systems engineering process using the Systems Modeling Language. It defines a set of principles built upon by the theoretical approach described in the InfoTech 2013 ISHM paper titled "Goal-Function Tree Modeling for Systems Engineering and Fault Management" presented by Dr. Stephen B. Johnson. Using the SysML language, the principles in this paper describe the expansion of the SysML language as a baseline in order to: hierarchically describe a system, describe that system functionally within success space, and allocate detection mechanisms to success functions for system protection

    Goal-Function Tree Modeling for Systems Engineering and Fault Management

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    The draft NASA Fault Management (FM) Handbook (2012) states that Fault Management (FM) is a "part of systems engineering", and that it "demands a system-level perspective" (NASAHDBK- 1002, 7). What, exactly, is the relationship between systems engineering and FM? To NASA, systems engineering (SE) is "the art and science of developing an operable system capable of meeting requirements within often opposed constraints" (NASA/SP-2007-6105, 3). Systems engineering starts with the elucidation and development of requirements, which set the goals that the system is to achieve. To achieve these goals, the systems engineer typically defines functions, and the functions in turn are the basis for design trades to determine the best means to perform the functions. System Health Management (SHM), by contrast, defines "the capabilities of a system that preserve the system's ability to function as intended" (Johnson et al., 2011, 3). Fault Management, in turn, is the operational subset of SHM, which detects current or future failures, and takes operational measures to prevent or respond to these failures. Failure, in turn, is the "unacceptable performance of intended function." (Johnson 2011, 605) Thus the relationship of SE to FM is that SE defines the functions and the design to perform those functions to meet system goals and requirements, while FM detects the inability to perform those functions and takes action. SHM and FM are in essence "the dark side" of SE. For every function to be performed (SE), there is the possibility that it is not successfully performed (SHM); FM defines the means to operationally detect and respond to this lack of success. We can also describe this in terms of goals: for every goal to be achieved, there is the possibility that it is not achieved; FM defines the means to operationally detect and respond to this inability to achieve the goal. This brief description of relationships between SE, SHM, and FM provide hints to a modeling approach to provide formal connectivity between the nominal (SE), and off-nominal (SHM and FM) aspects of functions and designs. This paper describes a formal modeling approach to the initial phases of the development process that integrates the nominal and off-nominal perspectives in a model that unites SE goals and functions of with the failure to achieve goals and functions (SHM/FM). This methodology and corresponding model, known as a Goal-Function Tree (GFT), provides a means to represent, decompose, and elaborate system goals and functions in a rigorous manner that connects directly to design through use of state variables that translate natural language requirements and goals into logical-physical state language. The state variable-based approach also provides the means to directly connect FM to the design, by specifying the range in which state variables must be controlled to achieve goals, and conversely, the failures that exist if system behavior go out-of-range. This in turn allows for the systems engineers and SHM/FM engineers to determine which state variables to monitor, and what action(s) to take should the system fail to achieve that goal. In sum, the GFT representation provides a unified approach to early-phase SE and FM development. This representation and methodology has been successfully developed and implemented using Systems Modeling Language (SysML) on the NASA Space Launch System (SLS) Program. It enabled early design trade studies of failure detection coverage to ensure complete detection coverage of all crew-threatening failures. The representation maps directly both to FM algorithm designs, and to failure scenario definitions needed for design analysis and testing. The GFT representation provided the basis for mapping of abort triggers into scenarios, both needed for initial, and successful quantitative analyses of abort effectiveness (detection and response to crew-threatening events)

    Rock magnetic and geochemical evidence for authigenic magnetite formation via iron reduction in coal-bearing sediments offshore Shimokita Peninsula, Japan (IODP Site C0020)

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    Sediments recovered at Integrated Ocean Drilling Program (IODP) Site C0020, in a fore‐arc basin offshore Shimokita Peninsula, Japan, include numerous coal beds (0.3–7 m thick) that are associated with a transition from a terrestrial to marine depositional environment. Within the primary coal‐bearing unit (∼2 km depth below seafloor) there are sharp increases in magnetic susceptibility in close proximity to the coal beds, superimposed on a background of consistently low magnetic susceptibility throughout the remainder of the recovered stratigraphic sequence. We investigate the source of the magnetic susceptibility variability and characterize the dominant magnetic assemblage throughout the entire cored record, using isothermal remanent magnetization (IRM), thermal demagnetization, anhysteretic remanent magnetization (ARM), iron speciation, and iron isotopes. Magnetic mineral assemblages in all samples are dominated by very low‐coercivity minerals with unblocking temperatures between 350 and 580°C that are interpreted to be magnetite. Samples with lower unblocking temperatures (300–400°C), higher ARM, higher‐frequency dependence, and isotopically heavy δ56Fe across a range of lithologies in the coal‐bearing unit (between 1925 and 1995 mbsf) indicate the presence of fine‐grained authigenic magnetite. We suggest that iron‐reducing bacteria facilitated the production of fine‐grained magnetite within the coal‐bearing unit during burial and interaction with pore waters. The coal/peat acted as a source of electron donors during burial, mediated by humic acids, to supply iron‐reducing bacteria in the surrounding siliciclastic sediments. These results indicate that coal‐bearing sediments may play an important role in iron cycling in subsiding peat environments and if buried deeply through time, within the subsequent deep biosphere

    NF01-450 Daylily Rust: A New Disease in the United States

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    This particular rust is very aggressive and destroys daylily foliage. So far all infections have been on the foliage; it is not known whether tuber infections occur

    Conceptual knowledge acquisition in biomedicine: A methodological review

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    AbstractThe use of conceptual knowledge collections or structures within the biomedical domain is pervasive, spanning a variety of applications including controlled terminologies, semantic networks, ontologies, and database schemas. A number of theoretical constructs and practical methods or techniques support the development and evaluation of conceptual knowledge collections. This review will provide an overview of the current state of knowledge concerning conceptual knowledge acquisition, drawing from multiple contributing academic disciplines such as biomedicine, computer science, cognitive science, education, linguistics, semiotics, and psychology. In addition, multiple taxonomic approaches to the description and selection of conceptual knowledge acquisition and evaluation techniques will be proposed in order to partially address the apparent fragmentation of the current literature concerning this domain

    Model-Based Data Integration and Process Standardization Techniques for Fault Management: A Feasibility Study

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    This paper describes the theory and considerations in the application of model-based techniques to assimilate information from disjoint knowledge sources for performing NASA's Fault Management (FM)-related activities using the TEAMS toolset. FM consists of the operational mitigation of existing and impending spacecraft failures. NASA's FM directives have both design-phase and operational-phase goals. This paper highlights recent studies by QSI and DST of the capabilities required in the TEAMS toolset for conducting FM activities with the aim of reducing operating costs, increasing autonomy, and conforming to time schedules. These studies use and extend the analytic capabilities of QSI's TEAMS toolset to conduct a range of FM activities within a centralized platform
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