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ホーム アーカイブ Thermal Letter 役員 今後の会合 国際伝熱会議の集会

ISBN : 0-85295-345-3

International Heat Transfer Conference 10
1994, 14-18 August, Brighton, UK

PREDICTING HEAT TRANSFER RATES IN TURBULENT GAS-SOLID FLOWS

Get access DOI: 10.1615/IHTC10.4340
pages 333-338

要約

Previous extensive experimental measurements of heat transfer rates in turbulent gas-solid flows have conclusively shown the dependence of these rates on local flow parameters, such as the local mean and rms velocity components of the two phases, as well as the local solids density. In this paper, a mathematical model for heat transfer in particle-laden, turbulent flows has been developed that builds on our recent hydrodynamic modelling work involving the turbulent transport of larger particles (Bolio et al., 1993). Temperature profiles and heat transfer coefficients are obtained from coupled thermal energy balances for the gas and particle phases. The flow predictions from our hydrodynamic analysis which treats velocity fluctuations in both phases and the corresponding interactions are applied directly to the heat transfer model. For the larger particles considered here, the particle velocity fluctuations, which can exceed gas velocity fluctuations, arc generated clue to particle-particle and particle-wall collisions and arc described by kinetic theory analogies. These particle interactions contribute to particle segregation in vertical pipe flow. In addition, conduction of thermal energy in the particle phase is augmented due to these particle velocity fluctuations as observed by Wang and Campbell (1992). It is clearly shown that these particle velocity fluctuations can give rise to the large heat transfer rates observed in practice in two-phase flow. We investigate the dependency of the heat transfer rate predictions on the various operating conditions and system parameters such as solids loading and particle size. Qualitative and quantitative comparisons of model predictions for heat transfer coefficients in vertical tubes are made with available experimental data.
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