Abstract
The paper presents a neural-network-based zonal method (RADNNET-ZM) for the analysis of radiative heat transfer in an arbitrary Cartesian enclosure with an isothermal, homogeneous, non-gray medium. The model accounts for the non-gray effect of absorbing species in a combustion environment and the geometric effect of any three-dimensional enclosures. The model is verified against benchmark solutions. Maximum local error is observed to be less than 4%. Prediction accuracy of an existing zonal radiation solver is assessed. Results demonstrate that RADNNET-ZM can provide a substantial improvement to zone fire simulation models for the prediction of radiative heat transfer without a significant increase in computation cost.
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Abbreviations
- a λ :
-
Local absorption coefficient
- A i :
-
Elemental area i
- D :
-
Grid size of discretization
- e λb :
-
Planck function
- f v :
-
Soot volume fraction
- F ij :
-
View factor between Ai and Aj
- F ss,xx :
-
Generic exchange factor (xx = pd, pp)
- L ij,xx :
-
Center-to-center distance between Ai and Aj (xx = pd, pp)
- L pd,x :
-
Mean beam length between two perpendicular elemental areas (x = soot, gas)
- L pp :
-
Mean beam length between two parallel elemental areas
- nx, ny, nz:
-
Dimensionless distances for Aj relative to Ai
- \(P_{{{\text{CO}}_{2} }}\) :
-
Partial pressure of CO2
- \(P_{{{\text{H}}_{2}{\text{O}} }}\) :
-
Partial pressure of H2O
- P g :
-
Total pressure of an N2/H2O/CO2 mixture
- \(\dot{q}_{\text{g}}^{\prime \prime }\) :
-
Incident heat flux due to emission of mixture medium
- \(\dot{q}_{\text{w}}^{\prime \prime }\) :
-
Incident heat flux due to emission of wall
- ss:
-
Surface–surface exchange factor
- SS:
-
Total surface–surface exchange factor
- T g :
-
Gas temperature
- T w :
-
Wall temperature
- \(X_{{{\text{CO}}_{2} }}\) :
-
Mole fraction of CO2
- X, Y, Z:
-
Dimensions of an enclosure
- α :
-
Total absorptivity (sum of soot and gas absorptivity)
- α s :
-
Soot absorptivity
- Δα:
-
Gas absorptivity
- β xx :
-
Normalized mean beam length (xx = pd, pp)
- λ :
-
Wavelength
- ε :
-
Emissivity of gas mixture
- σ :
-
Stefan–Boltzmann constant
- pd:
-
Perpendicular
- pp:
-
Parallel
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Acknowledgements
The authors would like to thank Kevin B. McGrattan for his constructive comments and valuable suggestions to this manuscript.
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Tam, W.C., Yuen, W.W. (2020). Assessment of Radiation Solvers for Fire Simulation Models Using RADNNET-ZM. In: Wu, GY., Tsai, KC., Chow, W.K. (eds) The Proceedings of 11th Asia-Oceania Symposium on Fire Science and Technology. AOSFST 2018. Springer, Singapore. https://doi.org/10.1007/978-981-32-9139-3_10
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DOI: https://doi.org/10.1007/978-981-32-9139-3_10
Publisher Name: Springer, Singapore
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