A Critical Review of Fire Tests and Safety Systems in Road Tunnels: Limitations and Open Points
Abstract
:1. Introduction
- ➢
- Q1. What are the basic characteristics of the fire test models that have been developed in the scientific community?
- ➢
- Q2. What are the positive aspects of the interaction of safety systems in road tunnels?
- ➢
- Q3. What are the negative aspects of the interaction of safety systems in road tunnels?
2. Background
3. Materials and Methods
- (1)
- Identify sources of information for the research material, such as databases, registers, and websites;
- (2)
- Select the literature based on content filtering according to the purpose stated in the abstract;
- (3)
- Establish eligibility criteria for the review and synthesis group in line with the research scope;
- (4)
- Conduct a full review of articles, including meta-analysis.
3.1. Information Sources
- (1)
- Definition of scope: Fire tests in road tunnels;
- (2)
- Databases and time frame: Scopus and Web of Science, from 2013 to 2022;
- (3)
- Eligibility criteria: Performance criteria were established for the abstract review;
- (4)
- Categorization: After the selection process, each article was assigned to a specific category or trend.
3.2. Selection Process: Formulation and Databases
3.3. Eligibility
3.4. Full-Text Review
4. Bibliometric Findings
4.1. Sources
4.2. Country Distribution
4.3. Articles over Time
4.4. Highly Cited Papers
4.5. Subcategories and Targets
5. Results
5.1. T.1 Fire Suppression
5.1.1. T.1.1. Model-Scale Test
5.1.2. T.1.2. Smoke Dynamics
5.1.3. T.1.3. Products of Combustion
5.2. T.2 Ventilation Systems
5.2.1. T.2.1. Natural Ventilation
5.2.2. T.2.2. Forced Ventilation
5.3. T.3 Water-Based Firefighting System
5.3.1. T.3.1. Water Mist and Water Spray
5.3.2. T.3.2. Automatic Sprinkler
6. Discussion
- In this study, we collected 72 articles about fire tests and safety systems, which mostly show the complex interaction between longitudinal ventilation and water-based firefighting systems;
- Q1. The basic characteristics of fire test models developed in the scientific community to date are related to the construction of simulated tunnels using computational fluid dynamics;
- Q2. The positive aspects of the interaction of safety systems in road tunnels are the contemporary use of ventilation systems and extinguishing solutions to reduce the power of fire and help people evacuate;
- Q3. The negative aspects of the interaction of safety systems in road tunnels are related to the technical elements of the design and the lack of communication between individual systems when a fire occurs. Resolving this issue may require improving the design of the devices, as well as on-site or simulated scenario testing to demonstrate the efficiency of the integrated system;
- Most of the collected articles are conceptual, and simulations of fire in tunnels are more economical and easier to perform than on-site fire tests. Theoretical approaches and analyses of fire development are essential to understand the phenomenon and setting up safety systems;
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
Document | Title | Year | Code |
[39] | Model-scale tunnel fire tests with automatic sprinkler | 2013 | T.3.2 |
[66] | Study of smoke backlayering during suppression in tunnels | 2013 | T.1.2 |
[68] | Experimental studies on smoke movement in a model tunnel with longitudinal ventilation | 2013 | T.1.2 |
[44] | Testing the predictive capabilities of evacuation models for tunnel fire safety analysis | 2013 | T.1.1 |
[106] | Fixed Fire Protection Systems in Tunnels: Issues and Directions | 2013 | T.3.2 |
[42] | Experimental and Numerical Study of the Interaction Between Water Mist and Fire in an Intermediate Test Tunnel | 2014 | T.3.1 |
[41] | Position of Maximum Ceiling Temperature in a Tunnel Fire | 2014 | T.1.1 |
[46] | Heat Release Rate of Heavy Goods Vehicle Fire in Tunnels with Fixed Water-Based Firefighting System | 2014 | T.3.1 |
[56] | Limit-Based Fire Hazard Model for Evaluating Tunnel Life Safety | 2015 | T.1.1 |
[91] | Ventilation simulation of a large and complex road tunnel: A safe journey—E4 the Stockholm bypass project | 2015 | T.2.2 |
[65] | Model-based airflow controller design for fire ventilation in road tunnels | 2016 | T.1.2 |
[43] | Experimental study of the effectiveness of a water system in blocking fire-induced smoke and heat in reduced-scale tunnel tests | 2016 | T.3.1 |
[38] | Effect of cross section and ventilation on heat release rates in tunnel fires | 2016 | T.1.3 |
[105] | Large Scale Tunnel Fire Tests with Large Droplet Water-Based Fixed Fire Fighting System | 2016 | T.3.1 |
[40] | Full-scale measurements of the operation of fire ventilation in a road tunnel | 2017 | T.1.1 |
[89] | Smoke spreading characteristics during a fire in a shallow urban road tunnel with roof openings under a longitudinal external wind blowing | 2017 | T.2.2 |
[86] | Study of the critical velocity in tunnels with longitudinal ventilation and spray systems | 2017 | T.2.2 |
[82] | On the problem of ventilation control in case of a tunnel fire event | 2017 | T.2.2 |
[37] | Experimental investigation of pool fire behavior to different tunnel-end ventilation opening areas by sealing | 2017 | T.1.3 |
[81] | Numerical investigation of a tunnel fire under longitudinal ventilation | 2017 | T.2.2 |
[74] | Temperature distributions in an underground road tunnel: Effect of car fire heat release | 2017 | T.1.3 |
[51] | Interpretation of flow fields induced by water spray systems in reduced-scale tunnel fire experiments by means of CFD simulations | 2018 | T.1.1 |
[102] | Water spray flow rate effect on smoke temperature distribution under the ceiling in tunnel fires with longitudinal ventilation | 2018 | T.3.1 |
[73] | Influence of fire suppression on combustion products in tunnel fires | 2018 | T.1.3 |
[63] | Study on hot gases flow in case of fire in a road tunnel | 2018 | T.1.2 |
[55] | The Application of Support Vector Machine (SVM) Regression Method in Tunnel Fires | 2018 | T.1.1 |
[98] | CFD Simulations of the Interaction of the Water Mist Zone and Tunnel Fire Smoke in Reduced-scale Experiments | 2018 | T.3.1 |
[90] | Analysis on ventilation pressure of fire area in longitudinal ventilation of underground tunnel | 2018 | T.2.2 |
[64] | Measuring Air Speed with a Low-Power MEMS Ultrasonic Anemometer via Adaptive Phase Tracking | 2019 | T.1.2 |
[49] | Study of tunnel fires during construction using a model-scale tunnel | 2019 | T.1.1 |
[50] | The characteristics of under-ventilated pool fires in both model and medium-scale tunnels | 2019 | T.1.1 |
[97] | The effect of nozzle design on the fire heat release rates in tunnel deluge systems | 2019 | T.3.1 |
[92] | The effect of forced ventilation by using two movable fans on thermal smoke movement in a tunnel fire | 2019 | T.2.2 |
[96] | Experimental study of the effectiveness of a water mist segment system in blocking fire-induced smoke and heat in mid-scale tunnel tests | 2019 | T.3.1 |
[103] | Performance evaluation on fixed water-based firefighting system in suppressing large fire in urban tunnels | 2019 | T.3.1 |
[54] | Predictive Computational Fluid Dynamics Simulation of Fire Spread on Wood Cribs | 2019 | T.1.1 |
[104] | Large-scale tunnel fire tests with different types of large droplet fixed fire fighting systems | 2019 | T.3.1 |
[62] | Re-direction of smoke flow in inclined tunnel fires | 2019 | T.1.2 |
[45] | Experimental studies on the gas temperature and smoke back-layering length of fires in a shallow urban road tunnel with large cross-sectional vertical shafts | 2019 | T.1.2 |
[99] | Tunnel Fire Suppression Tests with Water Mist Fire Extinguishing System Containing an Additive | 2019 | T.3.1 |
[34] | Science Mapping of Tunnel Fires: A Scientometric Analysis-Based Study | 2020 | T.1.2 |
[87] | Analysis of experimental data on the effect of fire source elevation on fire and smoke dynamics and the critical velocity in a tunnel with longitudinal ventilation | 2020 | T.2.2 |
[78] | Theoretical and experimental studies on the fire-induced smoke flow in naturally ventilated tunnels with large cross-sectional vertical shafts | 2020 | T.2.1 |
[69] | Critical longitudinal ventilation velocity for smoke control in a tunnel induced by two nearby fires of various distances: Experiments and a revisited model | 2020 | T.1.2 |
[61] | Experimental approach to suppress smoke diffusion in sloped road tunnels | 2020 | T.1.2 |
[101] | Flow fields induced by longitudinal ventilation and water spray system in reduced-scale tunnel fires | 2020 | T.3.1 |
[57] | Experimental study of back-layering length and critical velocity in longitudinally ventilated tunnel fire with various rectangular cross-sections | 2021 | T.1.2 |
[72] | Experimental investigation on the smoke back-layering length in a branched tunnel fire considering different longitudinal ventilations and fire locations | 2021 | T.1.3 |
[58] | Full-scale experimental investigation on smoke spreading and thermal characteristic in a transversely ventilated urban traffic link tunnel | 2021 | T.1.2 |
[84] | Experimental and numerical studies on the smoke extraction strategies by longitudinal ventilation with shafts during tunnel fire | 2021 | T.2.2 |
[47] | Expanding the FDS Simulation Capabilities to Fire Tunnel Scenarios Through a Novel Multi-scale Model | 2021 | T.1.1 |
[59] | Study of the critical velocity of the tunnels using an analytical approach | 2021 | T.1.2 |
[93] | The combined effect of a water mist system and longitudinal ventilation on the fire and smoke dynamics in a tunnel | 2021 | T.3.1 |
[85] | Influence of longitudinal ventilation on the mass flow rate distribution of fire smoke flow in tunnels | 2021 | T.2.2 |
[60] | Study on temperature decay characteristics of fire smoke backflow layer in tunnels with wide-shallow cross-section | 2021 | T.1.2 |
[94] | Parametric study of design fires for tunnels with water-based fire suppression systems | 2021 | T.3.1 |
[48] | An experimental study on smoke back-layering and critical velocity in tunnel fires with canyon cross wind | 2021 | T.1.1 |
[88] | The maximum gas temperature rises beneath the ceiling in a longitudinal ventilated tunnel fire | 2021 | T.2.2 |
[75] | Characteristics of fire and smoke in the natural gas cabin of urban underground utility tunnels based on CFD simulations | 2021 | T.1.3 |
[70] | An experimental study on the intermittent flame ejecting behavior and critical excess heat release rate of carriage fires in tunnels with longitudinal ventilation | 2022 | T.1.3 |
[71] | Smart real-time forecast of transient tunnel fires by a dual-agent deep learning model | 2022 | T.1.3 |
[100] | Experimental and numerical study on the flow field of longitudinally ventilated tunnels with water spray system | 2022 | T.3.1 |
[80] | A coupled hybrid numerical study of tunnel longitudinal ventilation under fire conditions | 2022 | T.2.2 |
[76] | Study on smoke temperature profile in bifurcated tunnel fires with various bifurcation angles under natural ventilation | 2022 | T.2.1 |
[107] | Fire tests with automatic sprinklers in an intermediate-scale tunnel | 2022 | T.3.2 |
[83] | Critical velocity in point extraction for dual longitudinally ventilated tunnel fire | 2022 | T.2.2 |
[77] | Determination of smoke layer thickness using vertical temperature distribution in tunnel fires under natural ventilation | 2022 | T.2.1 |
[67] | Experimental investigation of mass loss rate and spatial temperature distribution of the pool fire in tunnel | 2022 | T.1.2 |
[52] | Numerical Study of Large-Scale Fire in Makkah’s King Abdulaziz Road Tunnel | 2022 | T.1.1 |
[79] | The influence of wind on smoke propagation to the lower layer in naturally ventilated tunnels | 2022 | T.2.1 |
[53] | Fractal Analysis of Tunnel Structural Damage Caused by High-Temperature and Explosion Impact | 2022 | T.1.1 |
[95] | Estimation of the effects of water mist system on the tunnel critical velocity due to smoke cooling | 2022 | T.3.1 |
References
- Sustainable Transport. Available online: https://sdgs.un.org/topics/sustainable-transport (accessed on 20 February 2023).
- United Nations. Take Action for the Sustainable Development Goals. Available online: https://www.un.org/sustainabledevelopment/sustainable-development-goals/ (accessed on 20 February 2023).
- Sathurshan, M.; Saja, A.; Thamboo, J.; Haraguchi, M.; Navaratnam, S. Resilience of Critical Infrastructure Systems: A Systematic Literature Review of Measurement Frameworks. Infrastructures 2022, 7, 67. [Google Scholar] [CrossRef]
- Mottahedi, A.; Sereshki, F.; Ataei, M.; Nouri Qarahasanlou, A.; Barabadi, A. The Resilience of Critical Infrastructure Systems: A Systematic Literature Review. Energies 2021, 14, 1571. [Google Scholar] [CrossRef]
- Zhang, X.; Wu, X.; Park, Y.; Zhang, T.; Huang, X.; Xiao, F.; Usmani, A. Perspectives of big experimental database and artificial intelligence in tunnel fire research. Tunn. Undergr. Space Technol. 2021, 108, 103691. [Google Scholar] [CrossRef]
- Casey, N. Fire incident data for Australian road tunnels. Fire Saf. J. 2020, 111, 102909. [Google Scholar] [CrossRef]
- Ingason, H.; Li, Y.Z.; Lönnermark, A. Tunnel Fire Dynamics, Tunnel Fire Dynamics; Springer: London, UK, 2015. [Google Scholar] [CrossRef]
- Vianello, C.; Fabiano, B.; Palazzi, E.; Maschio, G. Experimental study on thermal and toxic hazards connected to fire scenarios in road tunnels. J. Loss Prev. Process. Ind. 2012, 25, 718–729. [Google Scholar] [CrossRef]
- European Parliament and Council. Directive 2004/54/EC. Official Journal of the European Union. L.167, Bruxelles. Available online: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A32004L0054 (accessed on 20 February 2023).
- McGrattan, K.B. Fire Dynamics Simulator (Version 6): Technical Reference Guide (No. NIST SP 1018); National Institute of Standards and Technology: Gaithersburg, MD, USA, 2022. [Google Scholar] [CrossRef]
- McGrattan, K.B.; Forney, G.P. Fire Dynamics Simulator (Version 6): User’s Guide (No. NIST SP 1019); National Institute of Standards and Technology: Gaithersburg, MD, USA, 2022. [Google Scholar] [CrossRef]
- Wu, X.; Zhang, X.; Huang, X.; Xiao, F.; Usmani, A. A real-time forecast of tunnel fire based on numerical database and artificial intelligence. Build. Simul. 2022, 15, 511–524. [Google Scholar] [CrossRef]
- Koekkoek, E.J.W.; Booltink, H. Neural network models to predict soil water retention. Eur. J. Soil Sci. 1999, 50, 489–495. [Google Scholar] [CrossRef]
- Sayad, Y.O.; Mousannif, H.; Al Moatassime, H. Predictive modeling of wildfires: A new dataset and machine learning approach. Fire Saf. J. 2019, 104, 130–146. [Google Scholar] [CrossRef]
- Tetko, I.V.; Livingstone, D.J.; Luik, A.I. Neural network studies. 1. Comparison of overfitting and overtraining. J. Chem. Inf. Model. 1995, 35, 826–833. [Google Scholar] [CrossRef]
- de Vasconcelos, M.J.P.; Sllva, S.; Tome, M.; Alvim, M.; Perelra, J.M.C. Spatial prediction of fire ignition probabilities: Comparing logistic regression and neural networks. Photogramm. Eng. Remote Sens. 2001, 67, 73–81. [Google Scholar]
- Dubey, V.; Kumar, P.; Chauhan, N. Forest Fire Detection System Using IoT and Artificial Neural Network; Springer: Singapore, 2021. [Google Scholar]
- Gong, L.; Jiang, L.; Li, S.; Shen, N.; Zhang, Y.; Sun, J. Theoretical and experimental study on longitudinal smoke temperature distribution in tunnel fires. Int. J. Therm. Sci. 2016, 102, 319–328. [Google Scholar] [CrossRef]
- Njå, O.; Svela, M. A review of competencies in tunnel fire response seen from the first responders’ perspectives. Fire Saf. J. 2007, 97, 137–145. [Google Scholar] [CrossRef]
- Roth, W.; Stirbys, A. Claims and Forensic Engineering in Tunneling. Fourth Forensic Eng. Congr. 2006, 217, 591–604. [Google Scholar] [CrossRef]
- Lin, C.L.; Chien, C.F. Lessons learned from critical accidental fires in tunnels. Tunn. Undergr. Space Technol. 2021, 113, 103944. [Google Scholar] [CrossRef]
- PRISMA. Prisma—Transparent Reporting of Systematic Reviews and Meta-Analyses. Available online: http://prisma-statement.org/ (accessed on 30 November 2022).
- Rethlefsen, M.L.; Kirtley, S.; Waffenschmidt, S.; Ayala, A.P.; Moher, D.; Page, M.J.; Koffel, J.B.; PRISMA-S Group. PRISMA-S: An extension to the PRISMA Statement for Reporting Literature Searches in Systematic Reviews. Syst. Rev. 2021, 10, 39. [Google Scholar] [CrossRef]
- Burnham, J.F. Scopus database: A review. Biomed. Digit. Libr. 2006, 3, 1. [Google Scholar] [CrossRef]
- Mongeon, P.; Paul-Hus, A. The journal coverage of Web of Science and Scopus: A comparative analysis. Scientometrics 2016, 106, 213–228. [Google Scholar] [CrossRef]
- Frampton, G.K.; Livoreil, B.; Petrokofsky, G. Eligibility screening in evidence synthesis of environmental management topics. Environ. Evid. 2017, 6, 27. [Google Scholar] [CrossRef]
- Prisma Flow Diagram. Available online: https://www.prisma-statement.org//PRISMAStatement/FlowDiagram (accessed on 30 November 2022).
- Donthu, N.; Kumar, S.; Mukherjee, D.; Pandey, N.; Lim, W.M. How to conduct a bibliometric analysis: An overview and guidelines. J. Bus. Res. 2021, 133, 285–296. [Google Scholar] [CrossRef]
- Broadus, R.N. Toward a definition of “bibliometrics”. Scientometrics 1987, 12, 373–379. [Google Scholar] [CrossRef]
- Singh, S. How to Conduct and Interpret Systematic Reviews and Meta-Analyses. Clin. Transl. Gastroenterol. 2017, 8, e93. [Google Scholar] [CrossRef] [PubMed]
- Ellegaard, O.; Wallin, J.A. The bibliometric analysis of scholarly production: How great is the impact? Scientometrics 2015, 105, 1809–1831. [Google Scholar] [CrossRef]
- Van Eck, N.J.; Waltman, L.; Noyons, E.C.M.; Buter, R.K. Automatic term identification for bibliometric mapping. Scientometrics 2010, 82, 581–596. [Google Scholar] [CrossRef] [PubMed]
- Yu, Y.; Li, Y.; Zhang, Z.; Gu, Z.; Zhong, H.; Zha, Q.; Yang, L.; Zhu, C.; Chen, E. A bibliometric analysis using VOSviewer of publications on COVID-19. Ann. Transl. Med. 2020, 8, 816. [Google Scholar] [CrossRef] [PubMed]
- Li, J.; Liu, J. Science Mapping of Tunnel Fires: A Scientometric Analysis-Based Study. Fire Technol. 2020, 56, 2111–2135. [Google Scholar] [CrossRef]
- Waltman, L.; Calero-Medina, C.; Kosten, J.; Noyons, E.C.; Tijssen, R.J.; van Eck, N.J.; van Leeuwen, T.N.; van Raan, A.F.; Visser, M.S.; Wouters, P. The Leiden ranking 2011/2012: Data collection, indicators, and interpretation. J. Am. Soc. Inf. Sci. Technol. 2012, 63, 2419–2432. [Google Scholar] [CrossRef]
- Scimago Journal Rank. Available online: https://www.scimagojr.com/journalrank.php?category=2603 (accessed on 30 November 2022).
- Chen, C.-K.; Xiao, H.; Wang, N.-N.; Shi, C.-L.; Zhu, C.-X.; Liu, X.-Y. Experimental investigation of pool fire behavior to different tunnel-end ventilation opening areas by sealing. Tunn. Undergr. Space Technol. 2017, 63, 106–117. [Google Scholar] [CrossRef]
- Li, Y.Z.; Fan, C.G.; Ingason, H.; Lönnermark, A.; Ji, J. Effect of cross section and ventilation on heat release rates in tunnel fires. Tunn. Undergr. Space Technol. 2015, 51, 414–423. [Google Scholar] [CrossRef]
- Li, Y.Z.; Ingason, H. Model-scale tunnel fire tests with automatic sprinkler. Fire Saf. J. 2013, 61, 298–313. [Google Scholar] [CrossRef]
- Król, M.; Król, A.; Koper, P.; Wrona, P. Full scale measurements of the operation of fire ventilation in a road tunnel. Tunn. Undergr. Space Technol. 2017, 70, 204–213. [Google Scholar] [CrossRef]
- Li, Y.Z.; Ingason, H. Position of Maximum Ceiling Temperature in a Tunnel Fire. Fire Technol. 2014, 50, 889–905. [Google Scholar] [CrossRef]
- Blanchard, E.; Boulet, P.; Fromy, P.; Desanghere, S.; Carlotti, P.; Vantelon, J.P.; Garo, J.P. Experimental and Numerical Study of the Interaction Between Water Mist and Fire in an Intermediate Test Tunnel. Fire Technol. 2013, 50, 565–587. [Google Scholar] [CrossRef]
- Sun, J.; Fang, Z.; Tang, Z.; Beji, T.; Merci, B. Experimental study of the effectiveness of a water system in blocking fire-induced smoke and heat in reduced-scale tunnel tests. Tunn. Undergr. Space Technol. 2016, 56, 34–44. [Google Scholar] [CrossRef]
- Ronchi, E. Testing the predictive capabilities of evacuation models for tunnel fire safety analysis. Saf. Sci. 2013, 59, 141–153. [Google Scholar] [CrossRef]
- Guo, Q.; Zhu, H.; Yan, Z.; Zhang, Y.; Zhang, Y.; Huang, T. Experimental studies on the gas temperature and smoke back-layering length of fires in a shallow urban road tunnel with large cross-sectional vertical shafts. Tunn. Undergr. Space Technol. 2019, 83, 565–576. [Google Scholar] [CrossRef]
- Cheong, M.K.; Cheong, W.O.; Leong, K.W.; Lemaire, A.D.; Noordijk, L.M. Heat Release Rate of Heavy Goods Vehicle Fire in Tunnels with Fixed Water Based Firefighting System. Fire Technol. 2014, 50, 249–266. [Google Scholar] [CrossRef]
- Verda, V.; Borchiellini, R.; Cosentino, S.; Guelpa, E.; Tuni, J.M. Expanding the FDS Simulation Capabilities to Fire Tunnel Scenarios Through a Novel Multi-scale Model. Fire Technol. 2021, 57, 2491–2514. [Google Scholar] [CrossRef]
- Zhao, W.; Ouyang, R.; Ran, Q.; Chen, T.; Xu, Z.; Zou, M.; Fan, C. An experimental study on smoke back-layering and critical velocity in tunnel fires with canyon cross wind. J. Wind. Eng. Ind. Aerodyn. 2021, 209, 104477. [Google Scholar] [CrossRef]
- Yao, Y.; Li, Y.Z.; Lönnermark, A.; Ingason, H.; Cheng, X. Study of tunnel fires during construction using a model-scale tunnel. Tunn. Undergr. Space Technol. 2019, 89, 50–67. [Google Scholar] [CrossRef]
- Yao, Y.; Li, Y.Z.; Ingason, H.; Cheng, X. The characteristics of under-ventilated pool fires in both model and medium-scale tunnels. Tunn. Undergr. Space Technol. 2019, 87, 27–40. [Google Scholar] [CrossRef]
- Sun, J.; Fang, Z.; Beji, T.; Merci, B. Interpretation of flow fields induced by water spray systems in reduced-scale tunnel fire experiments by means of CFD simulations. Tunn. Undergr. Space Technol. 2018, 81, 94–102. [Google Scholar] [CrossRef]
- Guedri, K.; Abdoon, A.A.; Bagabar, O.S.; Oreijah, M.; Bouzid, A.; Munshi, S.M. Numerical Study of Large-Scale Fire in Makkah’s King Abdulaziz Road Tunnel. Fluids 2021, 7, 5. [Google Scholar] [CrossRef]
- Yang, Z.; Wang, L. Fractal Analysis of Tunnel Structural Damage Caused by High-Temperature and Explosion Impact. Buildings 2022, 12, 1410. [Google Scholar] [CrossRef]
- Janardhan, R.K.; Hostikka, S. Predictive Computational Fluid Dynamics Simulation of Fire Spread on Wood Cribs. Fire Technol. 2019, 55, 2245–2268. [Google Scholar] [CrossRef]
- Zhang, H.-T.; Gao, M.-X. The Application of Support Vector Machine (SVM) Regression Method in Tunnel Fires. Procedia Eng. 2018, 211, 1004–1011. [Google Scholar] [CrossRef]
- Gehandler, J.; Eymann, L.; Regeffe, M. Limit-Based Fire Hazard Model for Evaluating Tunnel Life Safety. Fire Technol. 2015, 51, 585–614. [Google Scholar] [CrossRef]
- Zhang, T.; Wang, G.; Li, J.; Huang, Y.; Zhu, K.; Wu, K. Experimental study of back-layering length and critical velocity in longitudinally ventilated tunnel fire with various rectangular cross-sections. Fire Saf. J. 2021, 126, 103483. [Google Scholar] [CrossRef]
- Han, J.; Liu, F.; Wang, F.; Weng, M.; Liao, S. Full-scale experimental investigation on smoke spreading and thermal characteristic in a transversely ventilated urban traffic link tunnel. Int. J. Therm. Sci. 2021, 170, 107130. [Google Scholar] [CrossRef]
- Yousefi, M.; Yousefi, M.; Safikhani, H.; Inthavong, K.; Bamdad, K. Study of the Critical Velocity of the Tunnels Using an Analytical Approach. Fire Saf. J. 2021, 123, 103372. [Google Scholar] [CrossRef]
- Zhang, T.; Wang, G.; Hu, H.; Huang, Y.; Zhu, K.; Wu, K. Study on temperature decay characteristics of fire smoke backflow layer in tunnels with wide-shallow cross-section. Tunn. Undergr. Space Technol. 2021, 112, 103874. [Google Scholar] [CrossRef]
- Kume, S.; Sistenich, C.; Wawrzyniak, F. Experimental approach to suppress smoke diffusion in sloped road tunnels. Fire Saf. J. 2020, 114, 103134. [Google Scholar] [CrossRef]
- Zhao, S.; Li, Y.Z.; Kumm, M.; Ingason, H.; Liu, F. Re-direction of smoke flow in inclined tunnel fires. Tunn. Undergr. Space Technol. 2019, 86, 113–127. [Google Scholar] [CrossRef]
- Król, A.; Król, M. Study on Hot Gases Flow in Case of Fire in a Road Tunnel. Energies 2018, 11, 590. [Google Scholar] [CrossRef]
- Ghahramani, A.; Zhu, M.; Przybyla, R.J.; Andersen, M.P.; Galicia, P.J.; Peffer, T.E.; Zhang, H.; Arens, E. Measuring Air Speed With a Low-Power MEMS Ultrasonic Anemometer via Adaptive Phase Tracking. IEEE Sens. J. 2019, 19, 8136–8145. [Google Scholar] [CrossRef]
- Jan, Š; Jan, Š; Lukáš, F.; Jiří, C.; Jiří, Z. Model-based airflow controller design for fire ventilation in road tunnels. Tunn. Undergr. Space Technol. 2016, 60, 121–134. [Google Scholar] [CrossRef]
- Ko, Y.J.; Hadjisophocleous, G.V. Study of smoke backlayering during suppression in tunnels. Fire Saf. J. 2013, 58, 240–247. [Google Scholar] [CrossRef]
- Liu, W.; Deng, L.; Wu, S.; Shi, C.; Hong, W. Experimental investigation of mass loss rate and spatial temperature distribution of the pool fire in tunnel. Tunn. Undergr. Space Technol. 2022, 129, 104688. [Google Scholar] [CrossRef]
- Yi, L.; Niu, J.; Xu, Z.; Wu, D. Experimental studies on smoke movement in a model tunnel with longitudinal ventilation. Tunn. Undergr. Space Technol. 2013, 35, 135–141. [Google Scholar] [CrossRef]
- Tang, F.; Deng, L.; Meng, N.; Mcnamee, M.; Van Hees, P.; Hu, L. Critical longitudinal ventilation velocity for smoke control in a tunnel induced by two nearby fires of various distances: Experiments and a revisited model. Tunn. Undergr. Space Technol. 2020, 105, 103559. [Google Scholar] [CrossRef]
- He, Q.; Tang, F.; Zhao, Y.; Hu, P.; Gu, M. An experimental study on the intermittent flame ejecting behavior and critical excess heat release rate of carriage fires in tunnels with longitudinal ventilation. Int. J. Therm. Sci. 2022, 176, 107483. [Google Scholar] [CrossRef]
- Zhang, X.; Wu, X.; Huang, X. Smart real-time forecast of transient tunnel fires by a dual-agent deep learning model. Tunn. Undergr. Space Technol. 2022, 129, 104631. [Google Scholar] [CrossRef]
- Yang, X.; Luo, Y.; Li, Z.; Guo, H.; Zhang, Y. Experimental investigation on the smoke back-layering length in a branched tunnel fire considering different longitudinal ventilations and fire locations. Case Stud. Therm. Eng. 2021, 28, 101497. [Google Scholar] [CrossRef]
- Li, Y.Z.; Ingason, H. Influence of fire suppression on combustion products in tunnel fires. Fire Saf. J. 2018, 97, 96–110. [Google Scholar] [CrossRef]
- Sweda, W.; Khalil, E.E.; Huzzayyin, O.A. Temperature Distributions in an Underground Road Tunnel: Effect of Car fire Heat Release. In Proceedings of the 55th AIAA Aerospace Sciences Meeting, Grapevine, TX, USA, 9–13 January 2017. [Google Scholar] [CrossRef]
- Wang, W.; Zhu, Z.; Jiao, Z.; Mi, H.; Wang, Q. Characteristics of fire and smoke in the natural gas cabin of urban underground utility tunnels based on CFD simulations. Tunn. Undergr. Space Technol. 2021, 109, 103748. [Google Scholar] [CrossRef]
- Lu, X.; Weng, M.; Liu, F.; Wang, F.; Han, J.; Cheung, S.C. Study on smoke temperature profile in bifurcated tunnel fires with various bifurcation angles under natural ventilation. J. Wind. Eng. Ind. Aerodyn. 2022, 225, 105001. [Google Scholar] [CrossRef]
- Tanno, A.; Oka, H.; Kamiya, K.; Oka, Y. Determination of smoke layer thickness using vertical temperature distribution in tunnel fires under natural ventilation. Tunn. Undergr. Space Technol. 2022, 119, 104257. [Google Scholar] [CrossRef]
- Guo, Q.; Zhu, H.; Zhang, Y.; Yan, Z. Theoretical and experimental studies on the fire-induced smoke flow in naturally ventilated tunnels with large cross-sectional vertical shafts. Tunn. Undergr. Space Technol. 2020, 99, 103359. [Google Scholar] [CrossRef]
- Galhardo, A.; Viegas, J.; Coelho, P.J. The influence of wind on smoke propagation to the lower layer in naturally ventilated tunnels. Tunn. Undergr. Space Technol. 2022, 128, 104632. [Google Scholar] [CrossRef]
- Álvarez-Coedo, D.; Ayala, P.; Cantizano, A.; Węgrzyński, W. A coupled hybrid numerical study of tunnel longitudinal ventilation under fire conditions. Case Stud. Therm. Eng. 2022, 36, 102202. [Google Scholar] [CrossRef]
- Stokos, K.; Lygidakis, G.; Nikolos, I.; Tsangaris, S. Numerical Investigation of a Tunnel Fire Under Longitudinal Ventilation. In Proceedings of the ASME 2017 International Mechanical Engineering Congress and Exposition, Tampa, FL, USA, 3–9 November 2017. [Google Scholar] [CrossRef]
- Sturm, P.; Beyer, M.; Rafiei, M. On the problem of ventilation control in case of a tunnel fire event. Case Stud. Fire Saf. 2017, 7, 36–43. [Google Scholar] [CrossRef]
- Jiang, X.; Wan, J.; Wang, Z.; Liu, M. Critical velocity in point extraction for dual longitudinally ventilated tunnel fire. Tunn. Undergr. Space Technol. 2022, 122, 104313. [Google Scholar] [CrossRef]
- Wang, M.; Guo, X.; Yu, L.; Zhang, Y.; Tian, Y. Experimental and numerical studies on the smoke extraction strategies by longitudinal ventilation with shafts during tunnel fire. Tunn. Undergr. Space Technol. 2021, 116, 104030. [Google Scholar] [CrossRef]
- Wang, J.; Fang, Z.; Tang, Z.; Yuan, J. Influence of longitudinal ventilation on the mass flow rate distribution of fire smoke flow in tunnels. Tunn. Undergr. Space Technol. 2021, 112, 103938. [Google Scholar] [CrossRef]
- Tang, Z.; Liu, Y.; Yuan, J.; Fang, Z. Study of the critical velocity in tunnels with longitudinal ventilation and spray systems. Fire Saf. J. 2017, 90, 139–147. [Google Scholar] [CrossRef]
- Liu, Y.; Fang, Z.; Tang, Z.; Beji, T.; Merci, B. Analysis of experimental data on the effect of fire source elevation on fire and smoke dynamics and the critical velocity in a tunnel with longitudinal ventilation. Fire Saf. J. 2020, 114, 103002. [Google Scholar] [CrossRef]
- Yao, Y.; He, K.; Peng, M.; Shi, L.; Cheng, X. The maximum gas temperature rises beneath the ceiling in a longitudinal ventilated tunnel fire. Tunn. Undergr. Space Technol. 2021, 108, 103672. [Google Scholar] [CrossRef]
- Tanaka, F.; Kawabata, N.; Ura, F. Smoke spreading characteristics during a fire in a shallow urban road tunnel with roof openings under a longitudinal external wind blowing. Fire Saf. J. 2017, 90, 156–168. [Google Scholar] [CrossRef]
- Li, J.; Li, Y.; Feng, X.; Li, J. Analysis on ventilation pressure of fire area in longitudinal ventilation of underground tunnel. In Proceedings of the IOP Conference Series: Materials Science and Engineering, Shanghai, China, 28–29 December 2017; Volume 322. [Google Scholar] [CrossRef]
- Brandt, R.; Lucchini, S. Ventilation simulation of a large and complex road tunnel: A safe journey—E4 the Stockholm bypass project. In Proceedings of the 16th Australasian Tunneling Conference, Sydney, Australia, 30 October–1 November 2017. [Google Scholar]
- Zhou, T.; Wang, X.; He, J.; Chen, Q.; Wang, J. The effect of forced ventilation by using two movable fans on thermal smoke movement in a tunnel fire. J. Wind. Eng. Ind. Aerodyn. 2018, 184, 321–328. [Google Scholar] [CrossRef]
- Liu, Y.; Fang, Z.; Tang, Z.; Beji, T.; Merci, B. The combined effect of a water mist system and longitudinal ventilation on the fire and smoke dynamics in a tunnel. Fire Saf. J. 2021, 122, 103351. [Google Scholar] [CrossRef]
- Li, Y.Z.; Ingason, H. Parametric study of design fires for tunnels with water-based fire suppression systems. Fire Saf. J. 2021, 120, 103107. [Google Scholar] [CrossRef]
- Deng, T.; Norris, S.; Sharma, R.N. Estimation of the effects of water mist system on the tunnel critical velocity due to smoke cooling. Tunn. Undergr. Space Technol. 2022, 120, 104299. [Google Scholar] [CrossRef]
- Li, Q.; Tang, Z.; Fang, Z.; Yuan, J.; Wang, J. Experimental study of the effectiveness of a water mist segment system in blocking fire-induced smoke and heat in mid-scale tunnel tests. Tunn. Undergr. Space Technol. 2019, 88, 237–249. [Google Scholar] [CrossRef]
- Tarada, F. The Effect of Nozzle Design on the Fire Heat Release Rates in Tunnel Deluge Systems. In Proceedings of the 18th International Symposium on Aerodynamics, Ventilation and Fire in Tunnels, Athens, Greece, 25–27 September 2019. [Google Scholar] [CrossRef]
- Wang, J.-H.; Nie, Q.-M.; Fang, Z.; Tang, Z. CFD Simulations of the Interaction of the Water Mist Zone and Tunnel Fire Smoke in Reduced-scale Experiments. Procedia Eng. 2018, 211, 726–735. [Google Scholar] [CrossRef]
- Yan, M.; Zhang, Z.; Liu, W.; Jiang, Y.; Li, P.; Yang, M. Tunnel Fire Suppression Tests with Water Mist Fire Extinguishing System Containing an Additive. In Proceedings of the 2019 9th International Conference on Fire Science and Fire Protection Engineering (ICFSFPE), Chengdu, China, 18–20 October 2019; pp. 1–4. [Google Scholar] [CrossRef]
- Deng, T.; Norris, S.; Sharma, R.N. Experimental and numerical study on the flow field of longitudinally ventilated tunnels with water spray system. Tunn. Undergr. Space Technol. 2022, 127, 104575. [Google Scholar] [CrossRef]
- Sun, J.; Tang, Z.; Fang, Z.; Beji, T.; Merci, B. Flow fields induced by longitudinal ventilation and water spray system in reduced-scale tunnel fires. Tunn. Undergr. Space Technol. 2020, 104, 103543. [Google Scholar] [CrossRef]
- Wang, J.; Xie, Z.; Lu, K.; Jiang, X.; Zhang, H. Water spray flow rate effect on smoke temperature distribution under the ceiling in tunnel fires with longitudinal ventilation. Tunn. Undergr. Space Technol. 2018, 79, 190–196. [Google Scholar] [CrossRef]
- Li, J.; Li, Y.; Bi, Q.; Chow, W.; Cheng, C.; To, C.; Chow, C. Performance evaluation on fixed water-based firefighting system in suppressing large fire in urban tunnels. Tunn. Undergr. Space Technol. 2019, 84, 56–69. [Google Scholar] [CrossRef]
- Ingason, H.; Li, Y.Z. Large scale tunnel fire tests with different types of large droplet fixed fire fighting systems. Fire Saf. J. 2019, 107, 29–43. [Google Scholar] [CrossRef]
- Ingason, H.; Li, Y.Z.; Appel, G.; Lundström, U.; Becker, C. Large Scale Tunnel Fire Tests with Large Droplet Water-Based Fixed Fire Fighting System. Fire Technol. 2016, 52, 1539–1558. [Google Scholar] [CrossRef]
- Mawhinney, J.R. Fixed Fire Protection Systems in Tunnels: Issues and Directions. Fire Technol. 2013, 49, 477–508. [Google Scholar] [CrossRef]
- Ingason, H.; Li, Y.Z.; Arvidson, M.; Jiang, L. Fire tests with automatic sprinklers in an intermediate scale tunnel. Fire Saf. J. 2022, 129, 103567. [Google Scholar] [CrossRef]
- Wu, X.; Park, Y.; Li, A.; Huang, X.; Xiao, F.; Usmani, A. Smart Detection of Fire Source in Tunnel Based on the Numerical Database and Artificial Intelligence. Fire Technol. 2021, 57, 657–682. [Google Scholar] [CrossRef]
- Hodges, J.L.; Lattimer, B.Y.; Luxbacher, K.D. Compartment fire predictions using transpose convolutional neural networks. Fire Saf. J. 2019, 108, 102854. [Google Scholar] [CrossRef]
Inclusion Criteria | Description |
---|---|
Keywords | Tunnel fire, ventilation system, longitudinal ventilation, tunnel fires, smoke back layering, natural ventilation, model-scale tests, CFD simulations, water-based firefighting system, automatic sprinkler, water mist |
Language | English |
Source type | Peer-reviewed articles published in Scopus or Web of Science |
Time interval | 2013–2022 |
Journals | H-Index | Quartile Citation |
---|---|---|
Buildings | 35 | Q1 |
Case Studies in Fire Safety | 9 | - |
Case Studies in Thermal Engineering | 47 | Q1 |
Energies | 111 | Q1 |
Fire Safety Journal | 85 | Q1 |
Fire Technology | 47 | Q1 |
Fluids | 18 | Q2 |
IEEE Sensors Journal | 132 | Q1 |
International Journal of Thermal Sciences | 127 | Q1 |
Journal of Beijing University of Technology | 17 | Q4 |
Journal of Wind Engineering and Industrial Aerodynamics | 115 | Q1 |
Procedia Engineering | 88 | - |
Tunnelling and Underground Space Technology | 113 | Q1 |
Safety Science | 125 | Q1 |
Conference Proceedings |
---|
AIAA SciTech Forum—55th AIAA Aerospace Sciences Meeting |
ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE) |
IOP Conference Series: Materials Science and Engineering |
International Conference on Fire Science and Fire Protection Engineering |
Australasian Tunneling Conference |
Country | Number |
---|---|
China | 35 |
Sweden | 12 |
Japan | 4 |
Italy, Poland, New Zealand, USA | 2 |
France, Saudi Arabia, UK, Australia, Iran, Greece, Canada, Egypt, Finland, Spain, Czech Republic, Portugal, Austria | 1 |
Rank | Title | Authors | Journal | Country | Number |
---|---|---|---|---|---|
1 | Experimental investigation of pool fire behavior to different tunnel-end ventilation opening areas by sealing [37] | Chang-kun Chen, Huang Xiao, Nan-nan Wang, Cong-ling Shi, Cong-xiang Zhu, Xuan-ya Liu | Tunnelling and Underground Space Technology | China | 65 |
2 | Effect of cross section and ventilation on heat release rates in tunnel fires [38] | Ying Zhen Li, Chuan Gang Fan, Haukur Ingason, Anders Lönnermark, Jie Ji | Tunnelling and Underground Space Technology | Sweden | 61 |
3 | Model-scale tunnel fire tests with automatic sprinkler [39] | Ying Zhen Li, Haukur Ingason | Fire Safety Journal | Sweden | 52 |
4 | Full-scale measurements of the operation of fire ventilation in a road tunnel [40] | Małgorzata Król, Aleksander Król, Piotr Koper, Paweł Wrona | Tunnelling and Underground Space Technology | Poland | 43 |
5 | Position of Maximum Ceiling Temperature in a Tunnel Fire [41] | Ying Zhen Li, Haukur Ingason | Fire Technology | Sweden | 42 |
6 | Experimental and Numerical Study of the Interaction Between Water Mist and Fire in an Intermediate Test Tunnel [42] | E. Blanchard, P. Boulet, P. Fromy, S. Desanghere, P. Carlotti, J.P. Vantelon, J.P. Garo | Fire Technology | France | 40 |
7 | Experimental study of the effectiveness of a water system in blocking fire-induced smoke and heat in reduced-scale tunnel tests [43] | Jiayun Sun, Zheng Fang, Zhi Tang, Tarek Beji, Bart Merci | Tunnelling and Underground Space Technology | China | 33 |
8 | Testing the predictive capabilities of evacuation models for tunnel fire safety analysis [44] | Enrico Ronchi | Safety Science | Italy | 30 |
9 | Experimental studies on the gas temperature and smoke back-layering length of fires in a shallow urban road tunnel with large cross-sectional vertical shafts [45] | Qinghua Guo, Hehua Zhu, Zhiguo Yan, Yao Zhang, Yinping Zhang, Tianrong Huang | Tunnelling and Underground Space Technology | China | 29 |
10 | Heat Release Rate of Heavy Goods Vehicle Fire in Tunnels with Fixed Water-Based Firefighting System [46] | M.K. Cheong, W.O. Cheong, K.W. Leong, A.D. Lemaire, L.M. Noordijk | Fire Technology | Japan | 27 |
Research Target | Sub-Targets | Code | Number of Articles |
---|---|---|---|
T.1 Fire Suppression | Model-scale Test | T.1.1 | 13 |
Smoke Dynamics and Critical Velocity | T.1.2 | 15 | |
Fire Location and Product of Combustion | T.1.3 | 8 | |
T.2 Ventilation System | Natural Ventilation | T.2.1 | 4 |
Forced Ventilation | T.2.2 | 13 | |
T.3 Water-Based Firefighting System | Water Mist and Water Spray | T.3.1 | 16 |
Automatic Sprinkler | T.3.2 | 3 |
Paragraph | Sub-Targets | Summary of Content |
---|---|---|
5.1 Fire Suppression | T.1.1 Model-scale Test | Model-scale tests are conducted to investigate the effect of fire suppression on combustion products and their influence on smoke dynamics during a fire. |
T.1.2 Smoke Dynamics and Critical Velocity | Smoke management and dynamics are related to the need for a ventilation system that can work optimally, with its characteristics adjusted to match the fire's characteristics, such as air velocity, thermal temperature, and smoke stratification. | |
T.1.3 Fire Location and Product of Combustion | Fire suppression systems are essential for reducing the quantity of combustion products, but sometimes model-scale tests are needed to determine their activation. | |
5.2 Ventilation System | T.2.1 Natural Ventilation | Natural ventilation is the basis for analytically and numerically understanding fire development in tunnels. |
T.2.2 Forced Ventilation | Longitudinal ventilation systems are the most commonly used in road tunnels. Their performance must consider major characteristics such as air velocity, smoke plume, and interaction with other systems. | |
5.3 Water-Based Firefighting System | T.3.1 Water Mist and Water Spray | Water mist systems are innovative and offer advantages for fire suppression in tunnels. Research has focused on studying the interaction between ventilation and suppression systems. |
T.3.2 Automatic Sprinkler | Automatic sprinklers are commonly used in industrial and civil buildings. These firefighting systems can also be used in tunnels, but it is important to clearly identify the parameters for optimal use. |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Lombardi, M.; Berardi, D.; Galuppi, M. A Critical Review of Fire Tests and Safety Systems in Road Tunnels: Limitations and Open Points. Fire 2023, 6, 213. https://doi.org/10.3390/fire6050213
Lombardi M, Berardi D, Galuppi M. A Critical Review of Fire Tests and Safety Systems in Road Tunnels: Limitations and Open Points. Fire. 2023; 6(5):213. https://doi.org/10.3390/fire6050213
Chicago/Turabian StyleLombardi, Mara, Davide Berardi, and Marta Galuppi. 2023. "A Critical Review of Fire Tests and Safety Systems in Road Tunnels: Limitations and Open Points" Fire 6, no. 5: 213. https://doi.org/10.3390/fire6050213
APA StyleLombardi, M., Berardi, D., & Galuppi, M. (2023). A Critical Review of Fire Tests and Safety Systems in Road Tunnels: Limitations and Open Points. Fire, 6(5), 213. https://doi.org/10.3390/fire6050213