Article ID Journal Published Year Pages File Type
661981 International Journal of Heat and Mass Transfer 2009 10 Pages PDF
Abstract

A neural network correlation, RAD-NNET, is developed to simulate the realistic effect of non-gray radiative absorption by a homogeneous mixture of combustion gases (CO2 and H2O) and soot using numerical data generated by RADCAL. RAD-NNET is then applied to assess the accuracy of some commonly accepted approximate approaches to evaluate radiative heat transfer in three-dimensional non-gray media. Results show that there are significant errors associated with the current approximate approaches. RAD-NNET can be readily implemented in commercial CFD codes to greatly enhance the accuracy of simulation of radiative heat transfer in practical engineering systems.

Related Topics
Physical Sciences and Engineering Chemical Engineering Fluid Flow and Transfer Processes
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