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Fires in road tunnels constitute complex scenarios with interactions between the fire, tunnel users and safety measures. More and more methodologies for risk analysis quantify the consequences of these scenarios with complex models. Examples for complex models are the computational fluid dynamics model Fire Dynamics Simulator (FDS) and the microscopic evacuation model FDS+Evac. However, the high computational effort of complex models often limits the number of scenarios in practice. To balance this drawback, the scenarios are often simplified. Accordingly, there is a challenge to consider complex scenarios in risk analysis.
To face this challenge, we improved the metamodel used in the methodology for risk analysis presented on ISTSS 2016. In general, a metamodel quickly interpolates the consequences of few scenarios simulated with the complex models to a large number of arbitrary scenarios used in risk analysis. Now, our metamodel consists of the projection array-based design, the moving least squares method, and the prediction interval to quantify the metamodel uncertainty. Additionally, we adapted the projection array-based design in two ways: the focus of the sequential refinement on regions with high metamodel uncertainties; and the combination of two experimental designs for FDS and FDS+Evac.
To scrutinise the metamodel, we analysed the effects of three sequential refinement steps on the metamodel itself and on the results of risk analysis. We observed convergence in both after the second step (ten scenarios in FDS, 192 scenarios in FDS+Evac). In comparison to ISTSS 2016, we then ran 20 scenarios in FDS and 800 scenarios in FDS+Evac. Thus, we reduced the number of scenarios remarkably with the improved metamodel. In conclusion, we can now efficiently integrate complex scenarios in risk analysis. We further emphasise that the metamodel is broadly applicable on various experimental or modelling issues in fire safety engineering.
Methodologies on fire risk analysis in road tunnels consider numerous factors affecting risks (risk indicators) and express the results by risk measures. But only few comprehensive studies on effects of risk indicators on risk measures are available. For this reason, this study quantifies the effects and highlights the most important risk indicators with the aim to Support further developments in risk analysis. Therefore, a system model of a road tunnel was developed to determine the risk measures.
The system model can be divided into three parts: the fire part connected to the fire model Fire Dynamics Simulator (FDS); the evacuation part connected to the evacuation model FDS+Evac; and the frequency part connected to a model to calculate the frequency of fires. This study shows that the parts of the system model (and their most important risk indicators) affect the risk measures in the following order: first, fire part (maximum heat release rate); second, evacuation part (maximum preevacuation time); and, third, frequency part (specific frequency of fire). The plausibility of These results is discussed with view to experiences from experimental studies and past fire incidents.
Conclusively, further research can focus on these most important risk indicators with the aim to optimise risk analysis.
Safety measures like tunnel emergency Ventilation Systems cause high financial costs. Hence, safety measures have to be chosen with the focus on the expected reduction of the consequences like fatalities or damage on structures and in conjunction with the investments. Since 2004, the European directive EU 2004/54/EC proposes therefore the application of risk assessments. Because the EU directive provides only few legal requirements on risk assessments, the methodologies developed on this basis have large differences. After one decade of intensive research, the comparative study now highlights common aspects and differences of several methodologies.
Probabilistic thermo-Mechanical analysis of a concrete tunnel lining subject to fire The probability distributions of the parameters related to the thermal analysis was considered in order to study the variability of the results and to carry out a reliability analysis. This assessment considered as random variables the thermo-mechanical properties of the concrete, the maximum heat release rate (HRR), the duration of the period of maximum HRR, the convective coefficient, the emissivity at the surface exposed to the fire, the air velocity within the tunnel, and the initial fire radius. The temperature-time curve was described by a correlation. An experimental design based on a Latin Hypercube Sampling algorithm was performed to define the input parameters to each analysis case. The definition of a limit state function based on the punctual strain status has permitted to carry out a reliability analysis.
In urban areas the demand for public transportation is constantly growing. Underground railway systems overcome the problem of limited space on the ground and are therefore one of the most powerful systems in urban public transportation. These facilities can be very complex and are used by a large amount of passengers. Therefore, it is important to maintain the safety for people and buildings. Especially in the case of fire or arson attack.
This paper focusses on a fire scenario in a complex subway station for different weather conditions. The purpose is to identify the influences of different weather conditions on the smoke spread and the ability of self-rescue in case of a burning luggage.
The evaluation of the fire simulations will focus on toxicity and visibility taking into account the FED concept.
In Europa kommen ca. 80 % der Brandtoten bei Wohnungsbränden ums Leben. Dabei sind Brände in Wohn- und Schlafzimmern besonders gefährlich. Einige Objekte, wie Polstermöbel und Fernseher, stellen im Brandfall eine besonders große Gefahr dar, da sie sich schon durch kleine Zündquellen, wie ein Feuerzeug oder eine Kerze, leicht entzünden lassen, eine hohe Wärmefreisetzungsrate haben und viel Rauch produzieren. Ein einzelnes Sofa kann in einem Raum einen Flashover erzeugen. Besonders im Kinderzimmer tritt oft eine Häufung an besonders gefährlichen Objekten wie Polstermöbeln, Matratzen und elektrischen Geräten auf. Da Kinder sich im Brandfall oft falsch verhalten sie verstecken sich an schwer zugänglichen Orten wie unter dem Bett oder im Schrank anstatt den Raum zu verlassen sind sie besonders gefährdet.