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An Application Of Investigation On Prediction Of Smoke Production In A Tunnel Fire By Using A Computer Simulation

Year 2014, Volume: 10 Issue: 1, 45 - 64, 01.04.2014

Abstract

Computational fluid dynamics (CFD) is nowadays widely used to simulate smoke spread and temperature distribution as well as ventilation measures in a fire scenario. It allows improving fire fighting strategies and precaution measures in order to suppress the fire as fast as possible and help people to evacuate. In recent years, it has become apparent that computational fluid dynamics (CFD) can play an important and useful role in fire safety problems. The application of CFD to fire problems is also known as field modeling. Field modeling is based on the fundamental laws which govern the fire phenomena. Therefore, it is a valuable alternative for experimental investigations and empirical correlations and can be applied as a predictive tool. In this paper, field modeling is applied to tunnel fires in order to predict the critical ventilation velocity. Saha modellemesi yangın olayını yöneten temel kanunlara bağlıdır. Bu nedenle deneysel araştırmalar ve ampirik korelasyonlar için değerli bir alternatiftir ve öngörülerde bulunmaya yardımcı olan bir araç olarak başvurulabilir. Bu çalışmada tünel yangınlarında kritik başvurulmuştur. havalandırma hızının tespit edilmesi maksadıyla saha modellemesine

References

  • Kevin B. McGrattan, Anthony Hamins, 2001, Numerical Simulation of the Howard Street Tunnel Fire, Fire Research Division Building and Fire Research Laboratory.
  • A.R.Nilsen, T.Log, 2009, Results from three models compared to full- scale tunnel fires tests Fire Safety Journal 44 (2009) 33– 49.
  • J. Collazo, J. Porteiro *, D. Patiño, J.L. Miguez, E. Granada, J. Moran, 2009, Simulation and experimental validation of a methanol burner, Fuel 88 (2009) 326–334.
  • I.S. Lowndesa, S.A. Silvestera,, D. Giddingsb, S. Pickeringb, A. Hassanb, E. Lester, 2007, The computational modelling of flame spread along a conveyor belt, Fire Safety Journal 42 (2007) 51–67.
  • F. Liu, J.X. Wen, 2002, The effect of turbulence modelling on the CFD simulation of buoyant diffusion flames, Fire Safety Journal 37 (2002) 125–150.
  • D. Rusch, L. Blum, A. Moser, T. Roesgen, 2008, Turbulence model validation for fire simulation by CFD and experimental investigation of a hot jet in crossflow, Fire Safety Journal 43 (2008) 429–441.
  • J.P. Kunsch, 2002, Simple model for control of fire gases in a ventilated tunnel, Fire Safety Journal 37 (2002) 67–81.
  • C.C. Hwang_, J.C. Edwards, 2005, The critical ventilation velocity in tunnel fires—a computer simulation, Fire Safety Journal 40 (2005) 213– 244.
  • Y. Wu, M.Z.A. Bakar, 2000, Control of smoke Flow in tunnel fires using longitudinal ventilation systems a study of the critical velocity, Fire Safety Journal 35 (2000) 363}390.
  • Sherman C.P. Cheunga, Richard K.K. Yuena,, G.H. Yeohb, Grace W.Y. Cheng, 2004, Contribution of soot particles on global radiative heat transfer in a two-compartment fire, Fire Safety Journal 39 (2004) 412–428.
  • Karim Van Maele, Bart Merci, 2008, Application of RANS and LES field simulations to predict the critical ventilation velocity in longitudinally ventilated horizontal tunnels, Fire Safety Journal 43 (2008) 598–609.

An Application Of Investigation On Prediction Of Smoke Production In A Tunnel Fire By Using A Computer Simulation

Year 2014, Volume: 10 Issue: 1, 45 - 64, 01.04.2014

Abstract

Saha modellemesi yangın olayını yöneten temel kanunlara bağlıdır. Bu nedenle deneysel araştırmalar ve ampirik korelasyonlar için değerli bir alternatiftir ve öngörülerde bulunmaya yardımcı olan bir araç olarak başvurulabilir. Bu çalışmada tünel yangınlarında kritik başvurulmuştur

References

  • Kevin B. McGrattan, Anthony Hamins, 2001, Numerical Simulation of the Howard Street Tunnel Fire, Fire Research Division Building and Fire Research Laboratory.
  • A.R.Nilsen, T.Log, 2009, Results from three models compared to full- scale tunnel fires tests Fire Safety Journal 44 (2009) 33– 49.
  • J. Collazo, J. Porteiro *, D. Patiño, J.L. Miguez, E. Granada, J. Moran, 2009, Simulation and experimental validation of a methanol burner, Fuel 88 (2009) 326–334.
  • I.S. Lowndesa, S.A. Silvestera,, D. Giddingsb, S. Pickeringb, A. Hassanb, E. Lester, 2007, The computational modelling of flame spread along a conveyor belt, Fire Safety Journal 42 (2007) 51–67.
  • F. Liu, J.X. Wen, 2002, The effect of turbulence modelling on the CFD simulation of buoyant diffusion flames, Fire Safety Journal 37 (2002) 125–150.
  • D. Rusch, L. Blum, A. Moser, T. Roesgen, 2008, Turbulence model validation for fire simulation by CFD and experimental investigation of a hot jet in crossflow, Fire Safety Journal 43 (2008) 429–441.
  • J.P. Kunsch, 2002, Simple model for control of fire gases in a ventilated tunnel, Fire Safety Journal 37 (2002) 67–81.
  • C.C. Hwang_, J.C. Edwards, 2005, The critical ventilation velocity in tunnel fires—a computer simulation, Fire Safety Journal 40 (2005) 213– 244.
  • Y. Wu, M.Z.A. Bakar, 2000, Control of smoke Flow in tunnel fires using longitudinal ventilation systems a study of the critical velocity, Fire Safety Journal 35 (2000) 363}390.
  • Sherman C.P. Cheunga, Richard K.K. Yuena,, G.H. Yeohb, Grace W.Y. Cheng, 2004, Contribution of soot particles on global radiative heat transfer in a two-compartment fire, Fire Safety Journal 39 (2004) 412–428.
  • Karim Van Maele, Bart Merci, 2008, Application of RANS and LES field simulations to predict the critical ventilation velocity in longitudinally ventilated horizontal tunnels, Fire Safety Journal 43 (2008) 598–609.
There are 11 citations in total.

Details

Primary Language Turkish
Journal Section Articles
Authors

Erinç Dobrucalı This is me

Publication Date April 1, 2014
Published in Issue Year 2014 Volume: 10 Issue: 1

Cite

APA Dobrucalı, E. . (2014). An Application Of Investigation On Prediction Of Smoke Production In A Tunnel Fire By Using A Computer Simulation. Journal of Naval Sciences and Engineering, 10(1), 45-64.