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- 저자 : Gravel, L . (검색결과 1 건)
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Numerical Simulation of Industrial Boilers
McKenty, F .,Gravel, L .,Camarero, R . 한국화학공학회 1999 Korean Journal of Chemical Engineering Vol.16 No.4
The numerical simulation of combustion aerodynamics is a topic that has been generating much interest in the past few years. Much research has been devoted to this field since the late 1960's, and many models of varying complexity were developed. However, most of the computational effort was devoted to the validation of these various models on experimental geometries. Furthermore, most of these models were only available within the framework of research codes : commercial CFD software offered only the most basic of models to their users. In recent years, with the advent of more powerful and affordable workstations, the feasibility of treating very large coupled problems became a reality. Consequently, the incentive for commercial CFD code developers to apply their product to the simulation of industrial combustion phenomena brought about a lot of activity in this field. The result was the possibility to include sophisticated modelling of this complex physical phenomena within the framework of commercial codes designed to solve flows in very large and complex geometries. This presentation will endeavour to show that by interfacing a commercial CFD package (Star-CD) with a research combustion model library we were able to successfully simulate several different types of industrial boilers and incinerators fired with different types of fuels (gas, oil, wood). Though precise measurements inside industrial boilers are difficult to obtain, comparisons with measurements taken at the various outlets show good agreement with the predicted values. Furthermore, the simulations predicted trouble spots within the apparatus that were in close agreement with the manufacturer's field observations. In short, the numerical simulation of industrial combustion is not only qualitative, in the sense that it can correctly predict trends, but is well on its way to being quantitatively correct.
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