975 resultados para Operating space diagram
Resumo:
Infrared optical-multilayer filters and materials were exposed to the space environment of low Earth orbit on LDEF. This paper summarizes the effects of that environment on the physical and optical properties of the filters and materials flown.
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Infrared optical-multilayer filters and materials were exposed to the space environment of low Earth for a period of nearly six years on the NASA Long Duration Exposure Facility (LDEF) mission. This report describes the effects of that environment on the physical and optical properties of filters and materials used in an experiment designed by the University of reading Infrared multilayer Laboratory. Results of the experiment comprise IR processed spectra both before (1983), and after (1990) exposure, in conjunction with unexposed control samples.
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The television studio play is often perceived as a somewhat compromised, problematic mode in which spatial and technological constraints inhibit the signifying and aesthetic capacity of dramatic texts. Leah Panos examines the function of the studio in the 1970s television dramas of socialist playwright Trevor Griffiths, and argues that the established verbal and visual conventions of the studio play, in its confined and ‘alienated’ space, connect with and reinforce various aspects of Griffiths's particular approach and agenda. As well as suggesting ways in which the idealist, theoretical focus of the intellectual New Left is reflexively replicated within the studio, Panos explores how the ‘intimate’ visual language of the television studio allows Griffiths to create a ‘humanized’ Marxist discourse through which he examines dialectically his dramatic characters' experiences, ideas, morality, and political objectives. Leah Panos recently completed her doctoral thesis, ‘Dramatizing New Left Contradictions: Television Texts of Ken Loach, Jim Allen, and Trevor Griffiths’, at the University of Reading and is now a Postdoctoral Researcher on the AHRC funded project, ‘Spaces of Television: Production, Site and Style’, which runs from July 2010 to March 2014.
Resumo:
With continually increasing demands for improvements to atmospheric and planetary remote-sensing instrumentation, for both high optical system performance and extended operational lifetimes, an investigation to access the effects of prolonged exposure of the space environment to a series of infrared interference filters and optical materials was promoted on the NASA LDEF mission. The NASA Long Duration Exposure Facility (LDEF) was launchd by the Space Shuttle to transport various science and technology experiments both to and from space, providing investigators with the opportunity to study the effects of the space environment on materials and systems used in space-flight applications. Preliminary results to be discussed consist of transmission measurements obtained and processed from an infrared spectrophotometer both before (1983) and after (1990) exposure compared with unexposed control specimens, together with results of detailed microscopic and general visual examinations performed on the experiment. The principle lead telluride (PbTe) and Zinc Sulphide (ZnS) based multilayer filters selected for this preliminary investigation consist of : an 8-12µm low pass edge filter, a 10.6µm 2.5% half bandwidth (HBW) double half-wave narrow bandpass filter, and a 10% HBW triple half-wave wide bandpass filter at 15µm. Optical substrates of MgF2 and KRS-5 (T1BrI) will also be discussed.
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This paper employs a state space system description to provide a pole placement scheme via state feedback. It is shown that when a recursive least squares estimation scheme is used, the feedback employed can be expressed simply in terms of the estimated system parameters. To complement the state feedback approach, a method employing both state feedback and linear output feedback is discussed. Both methods arc then compared with the previous output polynomial type feedback schemes.
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Infrared multilayer interference filters have been used extensively in satellite radiometers for about 15 years. Filters manufactured by the University of Reading have been used in Nimbus 5, 6, and 7, TIROS N, and the Pioneer Venus orbiter. The ability of the filters to withstand the space environment in these applications is critical; if degradation takes place, the effects would range from worsening of signal-to-noise performance to complete system failure. An experiment on the LDEF will enable the filters, for the first time, to be subjected to authoritative spectral measurements following space exposure to ascertain their suitability for spacecraft use and to permit an understanding of degradation mechanisms.
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Residual stress having been further reduced, selected infrared coatings composed of thin films of (PbTe/ ZnS (or ZnSe) can now be made which comply with the durability requirements of MIL-48616 whilst retaining transparency. Such improved durability is due to the sequence:- i) controlled deposition, followed by ii) immediate exposure to air, followed by iii) annealing in vacuo to relieve stress. (At the time of writing we assume the empiric procedure "exposure to air/annealing in vacuo" acts to relieve the inherent stresses of deposition). As part of their testing, representative sample filters prepared by the procedure are being assembled for the shuttle's 1st Long Duration Exposure Facility (to be placed in earth orbit for a considerable period and then recovered for analysis). The sample filters comprise various narrowband-designs to permit deduction of the constituent thin film optical properties. The Reading assembly also contains representative sample of the infrared crystals, glasses, thin-film absorbers and bulk absorbers, and samples of shorter-wavelength filters prepared similarly but made with Ge/SiO. Findings on durability and transparency after exposure will be reported.
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The Earth-directed coronal mass ejection (CME) of 8 April 2010 provided an opportunity for space weather predictions from both established and developmental techniques to be made from near–real time data received from the SOHO and STEREO spacecraft; the STEREO spacecraft provide a unique view of Earth-directed events from outside the Sun-Earth line. Although the near–real time data transmitted by the STEREO Space Weather Beacon are significantly poorer in quality than the subsequently downlinked science data, the use of these data has the advantage that near–real time analysis is possible, allowing actual forecasts to be made. The fact that such forecasts cannot be biased by any prior knowledge of the actual arrival time at Earth provides an opportunity for an unbiased comparison between several established and developmental forecasting techniques. We conclude that for forecasts based on the STEREO coronagraph data, it is important to take account of the subsequent acceleration/deceleration of each CME through interaction with the solar wind, while predictions based on measurements of CMEs made by the STEREO Heliospheric Imagers would benefit from higher temporal and spatial resolution. Space weather forecasting tools must work with near–real time data; such data, when provided by science missions, is usually highly compressed and/or reduced in temporal/spatial resolution and may also have significant gaps in coverage, making such forecasts more challenging.
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An input variable selection procedure is introduced for the identification and construction of multi-input multi-output (MIMO) neurofuzzy operating point dependent models. The algorithm is an extension of a forward modified Gram-Schmidt orthogonal least squares procedure for a linear model structure which is modified to accommodate nonlinear system modeling by incorporating piecewise locally linear model fitting. The proposed input nodes selection procedure effectively tackles the problem of the curse of dimensionality associated with lattice-based modeling algorithms such as radial basis function neurofuzzy networks, enabling the resulting neurofuzzy operating point dependent model to be widely applied in control and estimation. Some numerical examples are given to demonstrate the effectiveness of the proposed construction algorithm.
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This paper presents a controller design scheme for a priori unknown non-linear dynamical processes that are identified via an operating point neurofuzzy system from process data. Based on a neurofuzzy design and model construction algorithm (NeuDec) for a non-linear dynamical process, a neurofuzzy state-space model of controllable form is initially constructed. The control scheme based on closed-loop pole assignment is then utilized to ensure the time invariance and linearization of the state equations so that the system stability can be guaranteed under some mild assumptions, even in the presence of modelling error. The proposed approach requires a known state vector for the application of pole assignment state feedback. For this purpose, a generalized Kalman filtering algorithm with coloured noise is developed on the basis of the neurofuzzy state-space model to obtain an optimal state vector estimation. The derived controller is applied in typical output tracking problems by minimizing the tracking error. Simulation examples are included to demonstrate the operation and effectiveness of the new approach.
Resumo:
The modelling of a nonlinear stochastic dynamical processes from data involves solving the problems of data gathering, preprocessing, model architecture selection, learning or adaptation, parametric evaluation and model validation. For a given model architecture such as associative memory networks, a common problem in non-linear modelling is the problem of "the curse of dimensionality". A series of complementary data based constructive identification schemes, mainly based on but not limited to an operating point dependent fuzzy models, are introduced in this paper with the aim to overcome the curse of dimensionality. These include (i) a mixture of experts algorithm based on a forward constrained regression algorithm; (ii) an inherent parsimonious delaunay input space partition based piecewise local lineal modelling concept; (iii) a neurofuzzy model constructive approach based on forward orthogonal least squares and optimal experimental design and finally (iv) the neurofuzzy model construction algorithm based on basis functions that are Bézier Bernstein polynomial functions and the additive decomposition. Illustrative examples demonstrate their applicability, showing that the final major hurdle in data based modelling has almost been removed.