Consequence analysis of false fire detectionin road tunnels

Toshiaki Sakaguchi and Ichiro Nakahori, Sohatsu Systems Laboratory Inc.Bernhard Kohl and Oliver Senekowitsch, ILF Consulting Engineers

Alan Vardy, University of Dundee

Contents

• Background and objective of paper

• Regulations for fire detection in road tunnels

• False fire detection rate

• Fire emergency response

• Consequence analysis – valid detection

• Consequence analysis – false detection

• Conclusions

Background

• Regulations for fire detection vary around the world: calling out different fire detection times in Japan, Germany and Austria

• Different regulations lead to different technologies: leading to different false alarm rates unique to fire detectors

• Fire emergency response vary around the world and tunnels: implementing different ventilation strategies in Japan and Europe

Objective of paper

• Conduct risk assessment of different fire detection times

• Conduct risk assessment of different false alarm rates

• Conduct risk assessment of different ventilation strategies

Two methods are proposed in risk assessment:

1) deterministic (qualitative) method [Tunnel Safety Simulator]

2) probabilistic (quantitative) method [Tunnel Risk Model]

applied to a bi-directional traffic and longitudinal ventilation tunnel in Japan

Regulations for tunnel fire detection

• In Japan: a 0.5m2 plate, 2litre gasoline fire must be detected within 30sec (“30 sec rule”)

• In Germany: a 4.0m2 plate, 20litre gasoline fire under less than 6m/s air flow must be detected within 60sec (“60 sec rule”)

• In Austria: two 1m2 plates, 10llitre methylated spirits fire under less than 3m/s air flow must be detected within 90sec (“90 sec rule”)

False alarm rates

Fire detectors vary around the world: flame detector in Japan, and linear temperature cable in Europe

Extremely difficult to obtain false fire alarm rates in publications, and the following rates are investigated

• Once a year

• Once a month

• Once a week

• Once a day

Fire emergency response

• Notifying operators and emergency services• Providing information about fire source• Traffic restriction• Traffic control• Ventilation strategy: zero-flow in Japan, low-speed flow in Europe• Smoke extraction• Fire risk mitigation such as FFFS• …

In supervised tunnel, human operators undertake responses. In non-supervised tunnel, responses are undertaken automatically. In the paper, traffic control and ventilation strategy are considered. Smoke extraction and FFFS are left for future studies.

Methodical approach

Two different methods applied:

• Deterministic scenario-based approach (known as

qualitative method) widely used in Japan

select and simulate a limited number of specific fire

scenarios and assess results (“safe” or “fatal”)

• Probabilistic, system-based approach (known as

quantitative method) applied in several European countries

(e.g. Austrian Tunnel Risk Model)

develop and assess a representative set of scenarios;

considering a significant number of parameter variations

calculate overall risk (expected risk value)

Results of qualitative assessment of valid fire detection

• Evolution of air-flow velocity and jet-fan output in

“90 sec rule” with zero-flow strategy

Results of qualitative assessment of valid fire detection

• Smoke density evolution and path of escapee in “90

sec rule” with zero-flow strategy

30 sec rule and Zero-flow strategy 90 sec rule and Zero-flow strategy

Results of quantitative assessment of valid fire detection

• Definition of a model tunnel

Tunnel systemBidirectional tunnel

with 1 tunnel tube and 1 lane per direction

Emergency exits 6

Tunnel cross section Vaulted, 71m² (8.4 m diameter)

Traffic volume 1,040 vehicles/hour

Traffic mix69.5 % passenger cars

30.5 % HGV (incl. busses)

Traffic speed 80 km/h

Results of quantitative assessment of valid fire detection

Austrian Tunnel Risk Model: broad range of many different

scenarios with varying parameters, taken into account in a

statistical manner

• 3 fire sizes

• 9 traffic scenarios (3 different traffic loads combined with 3

different symmetry scenarios)

• Usually at least 3 fire locations (reduced to 1 fire location)

• Fire detection: 30 sec rule, 60 sec rule, and 90 sec rule

• Emergency response: zero-flow and low-speed flow strategies

Results of quantitative assessment of valid fire detection

• Fire risk in dependence of valid detection time and ventilation strategy

Risk assessment of false alarm rates

False alarm influences collision risk in two ways:

• Vehicles travelling inside tunnel have to stop if it has

internal traffic signals

• Vehicles approaching tunnel might be stopped by

external traffic signals

Both create a risk of rear-end collisions. TuRisMo has a

distinctive branch in the event tree that allows translation

of false alarm rate into modified probability of consective

accidents.

Results of quantitative assessment of false alarm rates• (Fire + collision) risk in dependence of false alarm rate and

detection time in low-speed flow ventilation

Results of quantitative assessment of false alarm rates

• (Fire + collision) risk in dependence of false alarm rate and detection time in zero-flow ventilation

Results of quantitative assessment of false alarm rates

• (Fire + collision) risk in dependence of false alarm rate and emergency ventilation strategy

Conclusions

• Overall risk depends more strongly on the emergency ventilation strategy than on the detection time• Overall risk dependency on false alarms is close to linear but once a day is significantly frequenct compared to once a week or once a month• A false alarm rate of approximately once a day can be as important as the difference between zero-flow and low-speed flow emergency response• In general, there is an inverse relationship between fire detection time and the frequency of false alarm. The consequence of false alarm needs to be considered carefully when attempting to design fire detection system that are both rapid and reliable

Thank you!