MODELLING OF RADIAL HEAT TRANSPORT IN WALL-COOLED PACKED BEDS CONFIDENCE INTERVALS OF ESTIMATED PARAMETERS AND CHOICE OF BOUNDARY CONDITIONS
作者:
J.G.H. BORKINK,
P.C. BORMAN,
K.R. WESTERTERP†,
期刊:
Chemical Engineering Communications
(Taylor Available online 1993)
卷期:
Volume 121,
issue 1
页码: 135-155
ISSN:0098-6445
年代: 1993
DOI:10.1080/00986449308936141
出版商: Taylor & Francis Group
关键词: Wall-cooled packed bed;Effective heat transport coefficient;Confidence interval;Cross-correlation;Boundary condition
数据来源: Taylor
摘要:
The heat transport in a wall-cooled packed tube in which a hot gas is cooled down is often described with a pseudo-homogeneous one-dimensional or two-dimensional model. Assuming a radially flat inlet temperature profile at the bed entrance can lead to erroneous results, if the actual profile at the entrance is curved. It can cause an apparent length dependence of the effective heat transport coefficients, the so called “length effect”. The reason being that the amount of heat entering the packed bed is overestimated, which is compensated for by higher values for the heat transport coefficients. Using a parabolic inlet temperature profile, as measured in the packed bed at a certain minimal bed length, eliminates the length dependence of the heat transport coefficients. An experimental investigation showed that for the gas flow rates applied. Peps= 52 to 785, a wall heat transfer coefficient αwhas to be used for modelling the heat transport with a two-dimensional model. Confidence intervals are given for the effective radial heat conductivity λe,rthe wall heat transfer coefficient αwand the overall heat transfer coefficient Uu,v. It is shown that λe,rand αware strongly cross-correlated and have large confidence intervals. Especially at low gas flow rates αwis difficult to determine accurately. The confidence intervals for Uu,vare much smaller. It is shown that although values for λe,rand αwcan scatter much for different measurements due to the cross-correlation of these coefficients, the scatter in Uu,vis reduced significantly if this coefficient is calculated with the so called “lump equation”
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