doi:10.3850/978-981-08-7724-8_12-03


Numerical Soot Modelling and Radiation in Fires


J. Zhang and M. Delichatsiosa

FireSERT, School of the Built Environment and Built Environment Research Institute, University of Ulster, Newtownabbey, BT37 0QB, Northern Ireland, UK.

am.delichatsios@ulster.ac.uk

ABSTRACT

A comprehensive methodology is presented for modelling soot and radiation in fires. A global soot formation and radiation model that has been implemented in two independent CFD laminar codes and validated against laminar flames data is extended to turbulent cases using conditional moment closure (CMC) concept. A CMC equation for the soot mass fraction was solved whereas conditional species and temperature were obtained from equilibrium calculations in the fuel lean region and frozen reaction calculations in the fuel rich region (alternatively Shvab Zel'dovich relations for the species can be used if the chemistry of the fuel is unknown as usually is the case in fires). The enthalpy as a function of the mixture fraction needed for the calculation of the specie and temperature is derived by using a normalized enthalpy (over its adiabatic value) defect equation where this normalized enthalpy is independent of the mixture fraction. The same methodology for calculating species concentrations and temperature in terms of the mixture fraction has to be used both in laminar and turbulent cases. For low soot concentrations, the mixture fraction for the gaseous specie follows a conserved scalar equation, whereas for high soot loading the gaseous mixture fraction equation includes a loss term due to production of soot. The turbulence model was applied to a 7.1cm porous burner of methane and ethylene pool fires. The predicted soot concentration is found to be in good agreement with the experimental data. In the present application, RANS equations have been used to calculate the flow properties but the methodology is also applicable when using a LES code.

Keywords: Soot, Flame radiation, Buoyant jets, Pool fires, Fires.


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