Assessment of Radiation Solver of Fire Simulation Models Using RADNNET-ZM
Wai Cheong Tam, Walter W. Yuen
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, inhomogeneous, 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 substantial improvement to zone fire simulation models for the prediction of radiative heat transfer without a significant increase in computation cost.
11th Asia-Oceania Symposium on Fire Science and Technology (AOSFST)
and Yuen, W.
Assessment of Radiation Solver of Fire Simulation Models Using RADNNET-ZM, 11th Asia-Oceania Symposium on Fire Science and Technology (AOSFST), Taipei, -1, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=925079
(Accessed December 9, 2023)