Abstract
A road tunnel is an enclosed space where backlayering of smoke produced by a fire can extend its damage beyond the part exposed to the fire. To realize a worry-free and safe infrastructure, emergency facilities in tunnels must be improved. Since it is difficult to uniformly apply improvement projects to all tunnels in the face of limited project budgets, it is necessary to prioritize projects to perform improvements systematically. As a method of efficiently conducting these projects, a statistical risk calculation method based on fire accident statistics obtained by defining individual tunnel fire accident risk as “(probability of occurrence of fire in a tunnel) × (loss),” has been proposed. This permits ranking the risk, allowing to set risk improvement project priorities. But to clarify risk improvement effects, medium to long-term observations are necessary. For human loss, which is the loss with the greatest impact on risk, a method of calculating change of potential risk by fire simulation and evacuation simulation has been proposed. But in order to calculate the potential risk of many tunnels, vast computing resources and long periods of time are needed. Therefore, another method was studied, using the results from a model tunnel, and performing evaluations linking fire simulations with evacuation simulations under a variety of conditions as a database. This paper introduces a potential risk calculation method suitable for individual tunnels based on the results of multiple regression analysis performed using these data.
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Abbreviations
- R :
-
Risk
- P :
-
Probability
- P t :
-
Probability of tunnel fire (cases/year)
- P f :
-
Probability of tunnel fire due to traffic accident (cases/year)
- P b :
-
Probability of tunnel fire due to vehicle breakdown (cases/year)
- L :
-
Tunnel length (m)
- H v :
-
Large vehicle mixing rate (vehicles/day)
- E :
-
Portal elevation (m)
- S :
-
Difference from the nationwide expressway tunnel average traffic speed(km/h)
- F T :
-
Traffic pattern factor (Two ways: 1, One way: 0)
- L D :
-
Death loss amount (yen/person)
- L d :
-
Injury loss amount (yen/person)
- I :
-
Impact (Loss)
- HRR:
-
Heat release rate (MW)
- T e :
-
Evacuation start time (s)
- D e :
-
Distance between emergency exits (m)
- S e :
-
Evacuation walking speed (m/s)
- i :
-
Inclination (%)
- W s :
-
Wind speed (m/s)
- E x :
-
Number of exits
- N :
-
Number of residual evacuees
- N o :
-
Number of residual evacuees for object tunnel
- T o :
-
Traffic volume of object tunnel
- T m :
-
Traffic volume of model tunnel
- n c :
-
Conversion factor for number of residual evacuees
References
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Yokota, M., Yamazaki, T., Kawabata, N., Imai, S. (2020). Potential Risks Assessment Method Using the Model Tunnel Associated with Japanese Expressway Tunnel Fires. In: Wu, GY., Tsai, KC., Chow, W.K. (eds) The Proceedings of 11th Asia-Oceania Symposium on Fire Science and Technology. AOSFST 2018. Springer, Singapore. https://doi.org/10.1007/978-981-32-9139-3_71
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DOI: https://doi.org/10.1007/978-981-32-9139-3_71
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