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Risk evaluation in road tunnels based on CFD results
Author(s) -
Peter Vidmar
Publication year - 2022
Publication title -
thermal science/thermal science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.339
H-Index - 43
eISSN - 2334-7163
pISSN - 0354-9836
DOI - 10.2298/tsci201108174v
Subject(s) - risk assessment , process (computing) , fire safety , computer science , risk analysis (engineering) , environmental science , computational fluid dynamics , engineering , business , computer security , aerospace engineering , operating system
Approaches to risk assessment in tunnelling and underground spaces were introduced in 2004 as a result of several serious accidents in tunnels such as Mont Blanc and Tauern Tunnel in 1999. The EU has published the minimum safety requirements for tunnels over 500 m on Trans-European Road Network. The risk assessment is mandatory and should cover all components of the system, i.e. infrastructure, operation, users and vehicles. The professional community has started using the quantitative risk assessment approach, where the crucial issue is the consequence analysis of fire scenarios in a tunnel. Fire development is a complex physical phenomenon and its calculation is time consuming, therefore, complex models have rarely been used in quantitative risk assessment approaches. This paper presents the methodology of integrating fast-processing risk assessment methods with time-consuming CFD methods for fire consequence analysis in the process of tunnel safety assessment. The main variables are soot density and temperature, which are analyzed in one-minute time steps during the fire. Human behavior is considered with the evacuation model, which is needed to evaluate fatalities during the fire process. The application of the methodology is presented based on the evaluation of the national tolerable risk for tunnel transport and compared with referenced EU risk criteria. Furthermore, the presented methodology links CFD simulation results and the quantitative risk assessment approach, still representing the collective risk with F-N curves.

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