Numerical Modeling of Soot for Buoyant-Driven Fires

G. H. Yeoh
Associate Professor, Australian Nuclear Science and Technology Organisation (ANSTO), Menai, Australia

S. C. P. Cheung
School of Aerospace, Mechanical and Manufacturing Engineering, RMIT University, Australia

Series: Mechanical Engineering Theory and Applications
BISAC: TEC009000

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Volume 10

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Special issue: Resilience in breaking the cycle of children’s environmental health disparities
Edited by I Leslie Rubin, Robert J Geller, Abby Mutic, Benjamin A Gitterman, Nathan Mutic, Wayne Garfinkel, Claire D Coles, Kurt Martinuzzi, and Joav Merrick

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In buoyant-driven fires, fine carbonaceous particles (soot), which are invariably produced in the flaming zone and dispersed in the smoke, can significantly augment the global radiation process. Luminous soot radiation, in general, constitutes a portion of the radiative heat loss of the total heat release rate. To aptly determine the distribution of soot particles, insights into the controlling physical and chemical mechanisms associated with the soot formation as well as soot oxidation are required. Practical models to predict soot concentration are presented within this article. Two case studies, one on the field modeling investigation on a two-room compartment fire while the other on a large scale free-standing fire, are chosen to demonstrate the prediction of soot concentration considering the Reynolds-Averaging Navier-Stokes (RANS) or Large Eddy Simulation (LES) frameworks.

Where details of the turbulent fluctuation can be dispensed with and the effects of the turbulence on the mean flow are usually sufficient to quantify the turbulent flow characteristics, the former approach would suffice especially information on the mean soot concentration is only required. Nevertheless, the latter approach can provide very detailed information about the fluid flow and heat transfer, thereby producing a more accurate realization while encapsulating the broad range of length and time scale. More importantly, it allows a deeper understanding on how the tightly coupled phenomena between the flow structures and chemical combustion processes can affect the local temporal soot distribution in order to better construct a more comprehensive soot model for buoyant-driven fires. (Imprint: Nova)

Introduction

Considerations in the Development of Predictive Models for Soot

Governing Equations of the Field Model

Combustion Modeling For Buoyant-Driven Fires

Radiation Modeling for Buoyant-Driven Fires

Soots Modeling for Buoyant-Driven Fires

Results and Discussion

RANS Framework for Two-Room Compartment Fire

LES Framework for Large Scale Free-Standing Fire

Conclusion

References

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