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Assessment of ventilation efficiency for emergency situations in subway systems by CFD modeling

  • Research Article
  • Indoor/Outdoor Airflow and Air Quality
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Abstract

The ventilation system is the strategic component of the subway systems when incidents involving heavy smoke occur in tunnels. Consequently, the purpose of this study is to investigate the ventilation efficiency in one of the most severe emergency scenario: train on fire (maximum heat release rate reaching 30 MW due to an ultra-fast fire) and stopped in the tunnel, the incident requiring passenger evacuation. Two ventilation strategies are taken into account: tunnel ventilation fan system (mid-tunnel fan plant located in separate construction) in conjunction with stations mechanical ventilation and end-of-station fan plants in conjunction with stations mechanical ventilation. The analysis is performed using computational fluid dynamics (CFD) modeling. The numerical model proposes an original approach based on the introduction of source terms in conservation equations for energy, carbon monoxide (CO) and carbon dioxide (CO2), in order to deal with the heat, CO, and CO2 due to fire. Equations expressing the conservation of CO and CO2 are specially added to the basic equations governing a turbulent non-isothermal airflow in the CFD model. This method allowed achieving values of velocity, temperature, CO and CO2 concentrations all over the computational domain. In addition, the modeling and simulation methodology complies faithfully to the real operation of the ventilation systems investigated in normal and emergency (fire) conditions. The results show that both ventilation alternatives taken into account lead to the secure evacuation of passengers all over the simulation time. The evacuation process toward the nearest station is not at all disturbed by too high air velocities, high temperatures or critical CO or CO2 concentrations.

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References

  • Chen CK, Zhu CX, Liu XY, Yu NH (2016). Experimental investigation on the effect of asymmetrical sealing on tunnel fire behavior. International Journal of Heat and Mass Transfer, 92: 55–65.

    Article  Google Scholar 

  • Chen F, Guo SC, Chuay HY, Chien SW (2003). Smoke control of fires in subway stations. Theoretical and Computational Fluid Dynamics, 16: 349–368.

    Article  MATH  Google Scholar 

  • Chen LF, Hu LH, Zhang XL, Zhang XZ, Zhang XC, Yang LZ (2015). Thermal buoyant smoke back-layering flow length in a longitudinal ventilated tunnel with ceiling extraction at difference distance from heat source. Applied Thermal Engineering, 78: 129–135.

    Article  Google Scholar 

  • Chow WK, Gao Y, Zhao JH, Dang JF, Chow CL, Miao L (2015). Smoke movement in tilted tunnel fires with longitudinal ventilation. Fire Safety Journal, 75: 14–22.

    Article  Google Scholar 

  • Gao R, Li A, Hao X, Lei W, Deng B (2012). Prediction of the spread of smoke in a huge transit terminal subway station under six different fire scenarios. Tunnelling and Underground Space Technology, 31: 128–138.

    Article  Google Scholar 

  • Hu LH, Fong NK, Yang LZ, Chow WK, Li YZ, Huo R (2007). Modeling fire-induced smoke spread and carbon monoxide transportation in a long channel: Fire Dynamics Simulator comparisons with measured data. Journal of Hazardous Materials, 140: 293–298.

    Article  Google Scholar 

  • Hu LH, Zhou JW, Huo R, Peng W, Wang HB (2008). Confinement of fire induced smoke and carbon monoxide transportation by air curtain in channels. Journal of Hazardous Materials, 156: 327–334.

    Article  Google Scholar 

  • Hu LH, Tang F, Yang D, Liu S, Huo R (2010). Longitudinal distributions of COconcentration and difference with temperature field in a tunnel fire smoke flow. International Journal of Heat and Mass Transfer, 53: 2844–2855.

    Article  MATH  Google Scholar 

  • Hu LH, Wu L, Lu K, Zhang X, Liu S, Qiu Z (2014). Optimization of emergency ventilation mode for a train on fire stopping beside platform of a metro station. Building Simulation, 7: 137–146.

    Article  Google Scholar 

  • Ingason H, Lönnermark A (2004). Recent achievements regarding measuring of time-heat and time-temperature development in tunnels. In: Proceedings of 1st International Symposium on Safe & Reliable Tunnels, Innovative European Achievements, Prague, Czech Republic, pp. 87–96.

    Google Scholar 

  • Ingason H, Li YZ, Lönnermark A (2015). Runehamar tunnel fire tests. Fire Safety Journal, 71: 134–149.

    Article  Google Scholar 

  • Jain S, Shashi, Kumar S (2011). Numerical studies on evaluation of smoke control system of underground metro rail transport system in India having jet injection system: A case study. Building Simulation, 4: 205–216.

    Article  Google Scholar 

  • Ji J, Wan H, Li K, Han J, Sun J (2015). A numerical study on upstream maximum temperature in inclined urban road tunnel fires. International Journal of Heat and Mass Transfer, 88: 516–526.

    Article  Google Scholar 

  • Kayili S (2005). CFD simulation of fire and ventilation in the stations of underground transportation systems. Master Thesis, Middle East Technical University, Turkey.

    Google Scholar 

  • Kumm M (2010). Carried fire load in mass transport systems—A study of occurrence, allocation and fire behavior of bags and luggage in metro and commuter trains in Stockholm. Research Report, Mälardalen University, Västerås, Sweden.

    Google Scholar 

  • Launder BE, Spalding DB (1974). The numerical computation of turbulent flows. Computer Methods in Applied Mechanics and Engineering, 3: 269–289.

    Article  MATH  Google Scholar 

  • Lee SR, Nam DG, Moriyama S (2007). A numerical study on the effect of smoke control systems in subway station fires. In: Proceedings of 7th Asia-Oceania Symposium on Fire Science and Technology, Hong Kong, China.

    Google Scholar 

  • Li SKL, Kennedy WD (1999). A CFD analysis of station fire conditions in the Buenos Aires Subway System. ASHRAE Transactions, 105(1): 410–413.

    Google Scholar 

  • Li Y, Nielsen PV (2011). CFD and ventilation research. Indoor Air, 21: 442–453.

    Article  Google Scholar 

  • Li YZ, Ingason H, Lönnermark A (2013). Correlations between different scales of metro carriage fire tests. Research Report, SPTechnical Research Institute of Sweden, Borås, Sweden.

    Google Scholar 

  • Luo N, Li A, Gao R, Song T, Zhang W, Hu Z (2014). Performance of smoke elimination and confinement with modified hybrid ventilation for subway station. Tunnelling and Underground Space Technology, 43: 140–147.

    Article  Google Scholar 

  • Mao J, Xi YH, Bai G, Fan HM, Ji HZ (2011). A model experimental study on backdraught in tunnel fires. Fire Safety Journal, 46: 164–177.

    Article  Google Scholar 

  • Meng N, Hu L, Wu L, Yang L, Zhu S, Chen L, Tang W (2014). Numerical study on the optimization of smoke ventilation mode at the conjunction area between tunnel track and platform in emergency of a train fire at subway station. Tunnelling and Underground Space Technology, 40: 151–159.

    Article  Google Scholar 

  • Murakami H (2000). Underground: The Tokyo Gas Attack and the Japanese Psyche. New York: Vintage.

    Google Scholar 

  • NFPA (2014). NFPA Standard 130: Standard for Fixed Guideway Transit and Passenger Rail Systems, 2014 edn. Quincy, MA, USA: National Fire Protection Association.

    Google Scholar 

  • NFPA (2015). NFPA Standard 204: Standard for Smoke & Heat Venting, 2015 edn. Quincy, MA, USA: National Fire Protection Association.

    Google Scholar 

  • Roh JS, Ryou HS, Park WH, Jang YJ (2009). CFD simulation and assessment of life safety in a subway train fire. Tunnelling and Underground Space Technology, 24: 447–453.

    Article  Google Scholar 

  • Siegel R, Howell J (2002). Thermal Radiation Heat Transfer. New York: Taylor & Francis.

    Google Scholar 

  • Son BS, Chang HC (2008). Numerical predictions of fire characteristics of passenger train fire in an underground subway tunnel, depending on change of location of ventilation facility. Journal of Korean Institute of Fire Science & Engineering, 22: 1–8.

    Google Scholar 

  • Sørensen DN, Nielsen PV (2003). Quality control of computational fluid dynamics in indoor environments. Indoor Air, 13: 2–17.

    Article  Google Scholar 

  • Tanaka F, Majima S, Kato M, Kawabata N (2015). Performance validation of a hybrid ventilation strategy comprising longitudinal and point ventilation by a fire experiment using a model-scale tunnel. Fire Safety Journal, 71: 287–298.

    Article  Google Scholar 

  • Teodosiu C, Ilie V, Teodosiu R (2014). Appropriate CFD turbulence model for improving indoor air quality of ventilated spaces. Mathematical Modelling in Civil Engineering, 10: 28–42.

    Article  Google Scholar 

  • Wang F, Wang M (2016). A computational study on effects of fire location on smoke movement in a road tunnel. Tunnelling and Underground Space Technology, 51: 405–413.

    Article  Google Scholar 

  • Wang YF, Li YL, Yan PN, Zhang B, Jiang JC, Zhang L (2015). Maximum temperature of smoke beneath ceiling in tunnel fire with vertical shafts. Tunnelling and Underground Space Technology, 50: 189–198.

    Article  Google Scholar 

  • Wu GH, Han X, Liu QQ (2007). CFD analysis of fire characteristics on subway junction station. In: Proceedings of 1st International Symposium on Geotechnical Safety & Risk (ISGSR2007), Shanghai, China, pp. 793–802.

    Google Scholar 

  • Xi YH, Chow WK, Mao J (2015). Aerodynamics simulation on density jump in a long corridor fire. Tunnelling and Underground Space Technology, 50: 23–31.

    Article  Google Scholar 

  • Yuan FD, You SJ (2007). CFD simulation and optimization of the ventilation for subway side-platform. Tunnelling and Underground Space Technology, 22: 474–482.

    Article  Google Scholar 

  • Zhang B, Zhang J, Lu S, Li C (2015). Buoyancy-driven flow through a ceiling aperture in a corridor: A study on smoke propagation and prevention. Building Simulation, 8: 701–709.

    Article  Google Scholar 

  • Zhou R, Zhang W (2012). Analysis and optimization of ventilation mode of smoke control system in subway station fires. Journal of Theoretical and Applied Information Technology, 44: 283–289.

    Google Scholar 

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Authors and Affiliations

  1. Faculty of Building Services and Equipment, Technical University of Civil Engineering, 122–124 Lacul Tei Bvd, Bucharest, 020396, Romania

    Catalin Ioan Teodosiu, Viorel Ilie & Raluca Smaranda Teodosiu

  2. Metroul S.A., 3 bis Gutenberg St, Bucharest, 050027, Romania

    Radu Gabriel Dumitru

Authors
  1. Catalin Ioan Teodosiu
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  2. Viorel Ilie
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  3. Radu Gabriel Dumitru
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  4. Raluca Smaranda Teodosiu
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Correspondence to Catalin Ioan Teodosiu.

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Teodosiu, C.I., Ilie, V., Dumitru, R.G. et al. Assessment of ventilation efficiency for emergency situations in subway systems by CFD modeling. Build. Simul. 9, 319–334 (2016). https://doi.org/10.1007/s12273-015-0269-9

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  • DOI: https://doi.org/10.1007/s12273-015-0269-9

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