Application of an Optimized SLW Model in CFD Simulation of a Furnace

Masoud Darbandi (), Bagher Abrar and Gerry E. Schneider
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Masoud Darbandi: Sharif University of Technology, Department of Aerospace Engineering, Center of Excellence in Aerospace Systems
Bagher Abrar: Sharif University of Technology, Department of Aerospace Engineering, Center of Excellence in Aerospace Systems
Gerry E. Schneider: University of Waterloo, Department of Mechanical and Mechatronics Engineering

A chapter in Mathematical and Computational Approaches in Advancing Modern Science and Engineering, 2016, pp 389-399 from Springer

Abstract: Abstract Radiation is the most important part of heat transfer Heat transfer in combustion Combustion processes in applications such as furnaces. A proper radiation Radiation model for CFD CFD simulations is the one, which provides the required accuracy with minimum computational cost. In this work, we focus on radiation modeling in CFD simulation of a laboratory scaled furnace. We use an optimized spectral line-based weighted-sum-of-gray-gases (SLW) SLW model, which only needs four radiation transfer equations (RTE) RTE solution for accurate prediction of radiative heat transfer in non-gray Non-gray combustion fields. This is while the classic non-optimized SLW model needs at least 10–20 RTEs solution for the same case. We apply both the optimized and non-optimized SLW model to CFD CFD simulation of the furnace. To evaluate the achieved results, we compare them with available measured data. We further compare the results of optimized SLW model with those of non-optimized SLW model. The comparisons demonstrate that the optimized SLW model provides the same accuracy of non-optimized SLW mode, while it requires less than 80% computational time.

Keywords: Computational Fluid Dynamic; Mixture Fraction; Computational Fluid Dynamic Simulation; Radiation Radiation; Flow Governing Equation (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-30379-6_36

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DOI: 10.1007/978-3-319-30379-6_36

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