Fire Smoke Transport and Opacity Reduced-Order Model (Fire-STORM): A New Computer Model for High-Rise Fire Smoke Simulations

  • Serhat Bilyaz
  • Ofodike A. EzekoyeEmail author


The problem of smoke spread through elevator shafts in high rise buildings is analyzed theoretically and numerically in this paper. While experiments and computational fluid dynamics (CFD) models have been used for such exercises, there is a need for fast reduced-order models for such scenarios. Towards this goal, a transient network model called High-rise fire smoke transport and opacity reduced-order model (Fire-STORM) was developed to investigate heat and mass transfer through the elevator shaft during fires. The model numerically solves the coupled set of differential equations of the fire floor in conjunction with the steady state conservation equations of the elevator shaft. The model is validated in two stages. First, the stack effect in a non-fire scenario is analyzed. Pressure differences through exterior doors and elevator doors are compared with experimental data available in the literature and results of a computational fluid dynamics tool. Then, a first-floor fire scenario is considered for the same high-rise building in four different cases which are combinations of different building tightness and ambient temperatures. The results are compared with CFD simulations. For the four different building envelope and ambient thermal conditions, the soot mass fractions and optical visibilities were calculated and compared to CFD predictions. Overall, Fire-STORM is a simple and fast tool to model the evolution of heat and mass transfer in a high-rise building affected by fire. While Fire-STORM is excellent in predicting transient smoke transport for buildings with loose envelopes, it should be used with caution for buildings with tight envelopes since the errors for these cases are relatively high. Despite this, the relative computational speed difference between Fire-STORM and the CFD model highlights the utility of a reduced-order model for firefighter decision making and building control system design.


Fire Smoke High-rise CFD Model Transport Opacity 

List of symbols

\( \alpha \)

Thermal diffusivity

\( \alpha_{f} \)

Fire growth rate

\( C_{d} \)

Discharge coefficient

\( c_{p} \)

Constant pressure specific heat

\( c_{v} \)

Constant volume specific heat

\( \delta_{p} \)

Thermal penetration depth

\( g \)


\( H \)

Room height

\( h_{c} \)

Convective heat transfer coefficient

\( h_{r} \)

Radiative heat transfer coefficient

\( h_{t} \)

Total heat transfer coefficient

\( \Delta h_{c} \)

Heat of combustion

\( k \)

Thermal conductivity

\( K \)

Discharge loss coefficient


Light extinction coefficient


Mass extinction coefficient

\( \dot{m} \)

Mass flow rate


Number of elevator shafts


Kinematic viscosity


Nusselt Number


Gas constant



\( \Delta P \)

Pressure difference

\( Pr \)

Prandtl number

\( \dot{Q} \)

Heat transfer rate

\( \rho \)


\( Re_{D} \)

Reynolds number



\( T_{w} \)

Wall temperature

\( \sigma \)

Stefan Boltzmann constant



\( \chi_{s} \)

Soot yield


Soot mass fraction



\({\dot{\forall}} \)

Volumetric flow rate









Building envelope




Fire floor

\( HRR \)

Heat release rate


1st floor


17th floor








Elevator shaft


Shaft wall






\( CFD \)

Computational fluid dynamics


Effective leakage area


Fire dynamics simulator


Heating ventilating and air conditioning



This work was funded by the Federal Emergency Management Agency’s Assistance to Fire-Fighters Grant Program under Grant EMW-2016-FP-00833. The authors thank Dr. Qize He for his comments.


  1. 1.
    Rein G (2013) 9/11 world trade center attacks: lessons in fire safety engineering after the collapse of the towers. Fire Technol 49:583–585.CrossRefGoogle Scholar
  2. 2.
    Gann RG, et al (2005) Reconstruction of the fires in the world trade center towers. Federal building and fire safety investigation of the world trade center disaster. In: NIST NCSTAR, vol 1Google Scholar
  3. 3.
    Hu L, Milke JA, Merci B (2017) Special issue on fire safety of high-rise buildings. Fire Technol 53(1):1–3CrossRefGoogle Scholar
  4. 4.
    Jin T (1978) Visibility through fire smoke. J Fire Flammabl 9(2):135–155Google Scholar
  5. 5.
    Jin T (2002) Visibility and human behavior in fire smoke. SFPE Handb Fire Prot Eng 3:2–42Google Scholar
  6. 6.
    Purser DA (2015) Combustion toxicity. In Hurley MJ, et al. (eds) Chp 62 SFPE handbook of fire protection engineering. Springer, BerlinGoogle Scholar
  7. 7.
    Drysdale D (2011) An introduction to fire dynamics. Wiley, New YorkCrossRefGoogle Scholar
  8. 8.
    Tamura GT (1970) Computer analysis of smoke movement in tall buildings. Division of Building Research, National Research Council, OttawaGoogle Scholar
  9. 9.
    Klote JH (1989) Considerations of stack effect in building fires. National Institute of Standards and Technology, GaithersburgCrossRefGoogle Scholar
  10. 10.
    Walton G, Dols WS (2006) CONTAM 2.4 user guide and program documentation (No. NIST Interagency/Internal Report (NISTIR)-7251)Google Scholar
  11. 11.
    Qi D, WangL, Zmeureanu R (2015) Modeling smoke movement in shafts during high-rise fires by a multizone airflow and energy network program. ASHRAE Trans 121:242Google Scholar
  12. 12.
    Black WZ (2009) Smoke movement in elevator shafts during a high-rise structural fire. Fire Saf J 44(2):168–182MathSciNetCrossRefGoogle Scholar
  13. 13.
    Zhao G, Black W, Wang L (2017) Comparison of smoke management software and experimental measurements of smoke properties during a structural fire. In: ASHRAE 2017 winter conferenceGoogle Scholar
  14. 14.
    Wang LL, Black WZ, Zhao G (2013) Comparison of simulation programs for airflow and smoke movement during high-rise fires. ASHRAE Trans 119(2):1Google Scholar
  15. 15.
    Black WZ (2013) An integrated fire safety plan to manage smoke movement during a high-rise fire. ASHRAE Trans 119:146Google Scholar
  16. 16.
    Black WZ (2015) Stairwell pressurization and the movement of smoke during a high-rise fire. ASHRAE Trans 121:216Google Scholar
  17. 17.
    Black WZ (2010) COSMO—software for designing smoke control systems in high-rise buildings. Fire Saf J 45(6):337–348CrossRefGoogle Scholar
  18. 18.
    Black WZ (2011) Computer modeling of stairwell pressurization to control smoke movement during a high-rise fire. ASHRAE Trans 117(1):1Google Scholar
  19. 19.
    Qi D, Wang L, Zmeureanu R (2014) An analytical model of heat and mass transfer through non-adiabatic high-rise shafts during fires. Int J Heat Mass Transf 72:585–594CrossRefGoogle Scholar
  20. 20.
    Qi D, Wang L, Zmeureanu R (2017) The effects of non-uniform temperature distribution on neutral plane level in non-adiabatic high-rise shafts during fires. Fire Technol 53(1):153–172CrossRefGoogle Scholar
  21. 21.
    Qi D (2016) Analytical modeling of fire smoke spread in high-rise buildings. Concordia University, MontrealGoogle Scholar
  22. 22.
    Qi D, Wang LL, Zhao G (2017) Froude-Stanton modeling of heat and mass transfer in large vertical spaces of high-rise buildings. Int J Heat Mass Transf 115:706–716CrossRefGoogle Scholar
  23. 23.
    Zhang JY, Lu WZ, Huo R, Feng R (2008) A new model for determining neutral-plane position in shaft space of a building under fire situation. Build Environ 43(6):1101–1108CrossRefGoogle Scholar
  24. 24.
    Zhang X, Wang S, Wang J, Giacomo R (2014) A simplified model to predict smoke movement in vertical shafts during a high-rise structural fire. J Eng Sci Technol Rev 7(2):29CrossRefGoogle Scholar
  25. 25.
    Bae S, Ko GH, Lee CW, Ryou HS (2013) A network-based smoke control program with consideration of energy transfer in ultra-high-rise buildings, CAU_ESCAP. Build Simul 6(2):173–182CrossRefGoogle Scholar
  26. 26.
    Chen Y, Zhou X, Fu Z, Zhang T, Cao B, Yang L (2016) Vertical temperature distributions in ventilation shafts during a fire. Exp Therm Fluid Sci 79:118–125CrossRefGoogle Scholar
  27. 27.
    Hadjisophocleous G, Jia Q (2009) Comparison of FDS prediction of smoke movement in a 10-storey building with experimental data. Fire Technol 45(2):163–177CrossRefGoogle Scholar
  28. 28.
    Acikyol BH, Balik G, Kilic A (2016) Experimental investigation of the effect of fire protection lobby on stair pressurization system in a high-rise building. Fire Technol 1(53):135–151Google Scholar
  29. 29.
    Strege S, Ferreira M (2016) Characterization of stack effect in high-rise buildings under winter conditions, including the impact of stairwell pressurization. Fire Technol 10:211Google Scholar
  30. 30.
    McGrattan K, Hostikka S, McDermott R, Floyd J, Weinschenk C, Overholt K (2013) Fire dynamics simulator, user’s guide. NIST Spec Publ 1019:6th EditionGoogle Scholar
  31. 31.
    Quintiere JG (2006) Fundamentals of fire phenomena. Wiley Online Library, New YorkCrossRefGoogle Scholar
  32. 32.
    Ohlemiller TJ, Mulholland GW, Maranghides A, Filliben JJ, Gann RG (2005) Federal building and fire safety investigation of the World Trade Center disaster: fire tests of single office workstations. NIST NCSTAR 1-5C. National Institute of Standards and Technology, Gaithersburg, MDGoogle Scholar
  33. 33.
    Karlsson B, Quintiere J (1999) Enclosure fire dynamics. CRC Press, Boca RatonCrossRefGoogle Scholar
  34. 34.
    National Fire Protection Association (1995) 204M-guide for smoke and heat venting. Natl Fire Prot Assoc 995: 1Google Scholar
  35. 35.
    He Q, Ezekoye OA, Tubbs B, Baldassarra C (2015) CFD simulation of smoke spread through elevator shafts during fires in high rise buildings. In: ASME 2015 international mechanical engineering congress and exposition, pp V08AT10A045–V08AT10A045.Google Scholar
  36. 36.
    Committee AS, et al (2013) ASHRAE handbook: fundamentals 2013. ASHRAE, AtlantaGoogle Scholar
  37. 37.
    Emmerich SJ, Persily AK (1998) Energy impacts of infiltration and ventilation in US office buildings using multi-zone airflow simulation. Proc IAQ Energy 98:191–206Google Scholar
  38. 38.
    Jeong JW, Firrantello J, Bahnfleth WP, Freihaut JD, Musser A (2008) Case studies of building envelope leakage measurement using an air-handler fan pressurisation approach. Build Serv Eng Res Technol 29(2):137–155CrossRefGoogle Scholar
  39. 39.
    Klote JH, Ferreira MJ, Kashef A, Turnbull PG, Milke JA (2012) Handbook of smoke control engineering. American Society of Heating Refrigerating and Air-Conditioning Engineers, New DelhiGoogle Scholar
  40. 40.
    Tamura GT, Shaw CY (1976) Studies on exterior wall air tightness and air infiltration of tall buildings. ASHRAE Trans (United States) 82:122Google Scholar
  41. 41.
    Tamura GT, Shaw CY (1976) Air leakage data for the design of elevator and stair shaft pressurization systems. ASHRAE Trans 82(2):179–190Google Scholar
  42. 42.
    Tamura GT, Shaw CY (1978) Experimental studies of mechanical venting for smoke control in tall office buildings. Division of Building Research, National Research Council of Canada, OttawaGoogle Scholar
  43. 43.
    McGrattan K, Hostikka S, McDermott R, Floyd J, Weinschenk C, Overholt K (2015) NIST special publication 1018-1, fire dynamics simulator (version 6.2) technical reference guide, volume 1: mathematical model. National Institute of Standards and Technology, MarylandGoogle Scholar
  44. 44.
    U.S. Nuclear Regulatory Commission (2016) Verification and validation of selected fire models for nuclear power plant applications: supplement 1. Office of Nuclear Regulatory Research (RES), Washington, DC and Electric Power Research Institute (EPRI), Palo Alto, CA. NUREG-1824 Supplement 1 and EPRI 3002002182Google Scholar
  45. 45.
    Bergman TL, Incropera FP, Lavine AS (2011) Fundamentals of heat and mass transfer. Wiley, New YorkGoogle Scholar
  46. 46.
    Babrauskas V (1989) Smoke and gas evolution rate measurements on fire-retarded plastics with the cone calorimeter. Fire Saf J 14(3):135–142CrossRefGoogle Scholar
  47. 47.
    Babrauskas V, Krasny JF (2003) Upholstered furniture and mattresses. NFPA Fire Prot Handb Sect 8: 1Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringThe University of Texas at AustinAustinUSA

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