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Thuillier, G.; Christophe, J.; Azria, G.; Herse, M.; Fauliot, V.; Girod, F.; Fratter, C.; Thouvenin, J.P.; Solheim, B.H.
doi: 10.1177/003754979205900202pmid: N/A
The WINDII instrument (Wind Imaging Interferometer) is dedicated to the measurement of the temperature and wind in the upper Earth's atmosphere. It was launched with the NASA-UpperAtmosphere Research Satellite on September 12, 1991. It analyzes the natural emission lines of the atmosphere by an inteiferometric method to extract the temperature and wind information.Such a mission requires building the instrument, preparing its modes of operation, its scientific data processing, and evaluating its performance.To achieve these last tasks simulated data are needed. Which is why we have developed a quite extensive code of simulation which consists of several models: instrument, atmosphere to be observed (temperature, wind and intensity), orbit and attitude, and instrumental noises.The simulated data have permitted the evaluation of certain instrument effects and suggested some improvements of design. The effects of the various sources of noise have been studied. Scenarios of observations have been derived allowing the study of the scientific data processing algorithms and evaluation of their performances.Simulation of such a space instrument has been seen as an essential step in the design of the mission.
doi: 10.1177/003754979205900203pmid: N/A
In a plant, the size of a maintenance staff initst be related to the level of output. The optimal level of maintenance is essential for maximizing the output of the production process. This paper develops a simulation model to determine the size of a maintenance crew. The heart of the simulation model is the machine servicing model. The model is applied to a local soft drink plant to deter mine the optimal number of their mainte nance crew, and the result of the study is presented.
doi: 10.1177/003754979205900205pmid: N/A
A mathematical model is developed here for the impulse response of a class of systems represented by a general linear parabolic partial differential equation. Using a generalized eigenfuction expansion and the concept of a sampled-data system, a canonical set of state equations is obtained in discrete form. The impulse inputs may be any known time-varying functions on the given boundaries of the system or may be assumed to be distributed over a finite boundary region. For this computer model, no spatial discretization is required. Each discrete-time equation represents the dynamic behavior of each eigenvalue of the system and the response variable at any discrete location is given by a spatial linear combination of these state variables. Due to the discrete formulation of the system equations, numerical stability is assured. The equations are stable for any sampling time selected and the solution at any particular time desired may be simply obtained by incorporating this value directly into the model equations. The application of this method is demonstrated by solving a two-dimensional heat transfer problem subject to a single impulse input and comparisons were made to the finite element method of solution.
doi: 10.1177/003754979205900207pmid: N/A
The importance of accurate models for the input processes of simulation is generally recognized. However, the dependencies between the input processes have, at least in queueing network simulation, been paid little attention In this paper, we consider modeling the joint distribution of the input processes required in queueing network simulation Particularly, we propose a method for modeling the dependencies between service demands. In addition, we propose a method for dividing the service demand into service times per visit. These methods are important in simulation modeling of a computer system when accounting files provide the identification data. The experiments reported indicate that the proposed methods produce accurate estimates for quantiles of the system response-time distribution
doi: 10.1177/003754979205900208pmid: N/A
The issue of correctness of complex asyn chronorcs distributed algorithms imple mented on loosely coupled parallel processor systemsis difficult to address given the lack of effective debugging tools. In such systems, messages propagate asynchronously over physical connections and precise knowledge of the state of every message in the system at any instant of time is difficult to obtain. For a particular class of asynchronous distrib uted algorithrns [1,2,5] that may be charac terized by independent models that execute asynchronously on the processors and interact with one another only through explicit messages, the following reasoning applies. Information on the flow and content of messages and the activity of the processors is significant towards under standing the functional correctness of the implementation.This paper proposes a new approach , MADCAPP, to measure and analyze high- level message communication and the activity level of the processors.
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