Metamodel for complex scenarios in fire risk analysis of road tunnels

Abstract

The risk analysis of road tunnels faces a growing complexity in fire scenarios, e.g. caused by new energy carriers. Essentially, such complex scenarios involve many interactions between the tunnel users, the fire source and the safety measures. One example is the alarm of tunnel users either initiated by the perception of smoke or by the fire alarm system. To consider these interactions for the quantification of consequences, e.g. fatalities, risk analysis requires a complex model. However, the complex model can compute in practice only few discrete scenarios due to its high computational cost, whereas risk analysis generally needs the consequences of a high number of random scenarios. Metamodels can solve this contradiction. They are able to approximate the consequences of many random scenarios with low computational cost based on the consequences of few discrete scenarios computed with the complex model. The efficiency of metamodels depends on the required number of these discrete scenarios. In this sense, this dissertation proposes an efficient metamodel within an innovative methodology for risk analysis of road tunnels to allow to consider an increased complexity of scenarios. This metamodel applies the following methods or models: the projection array-based design method specifies the experimental design for the discrete scenarios; the combination of the fire model FDS and the microscopic evacuation model FDS+Evac constitutes the complex model; and moving least squares produces the response surface model. The response surface model approximates the consequences of the random scenarios and therewith introduces an uncertainty, called metamodel uncertainty, which is quantified with the prediction interval method. Additionally, stochastic individual characteristics of tunnel users in discrete scenarios computed with FDS+Evac attribute evacuation uncertainties to the consequences. An original development in this dissertation, the 'direct approach', directly transfers the evacuation uncertainties of the discrete scenarios to any random scenario. The evaluation of the metamodel in this dissertation shows following results. Firstly, the response surface model sufficiently represents the consequences of the complex model. Secondly, the metamodel uncertainty is also essential for this representation, but the prediction interval method reveals a drawback in the risk analysis. Potential approaches to deal with this drawback are discussed. Finally, the direct approach reproduces the evacuation uncertainty of the complex model which then clearly affects the consequences of random scenarios. Therefore, the consideration of the evacuation uncertainty plays an important role for the risk analysis. Furthermore, the projection array-based design method was adapted in this dissertation with two approaches, namely the combination of the experimental designs for FDS and FDS+Evac as well as their sequential refinement. Both approaches contribute to the efficiency of the metamodel. These results lead to following conclusions. Firstly, the metamodel efficiently integrates the consequences of discrete scenarios into risk analysis and thus allows to consider an increased complexity. Secondly, the metamodel is an advancement for risk analysis not only for road tunnels but also more general in fire safety engineering. For these two reasons, the metamodel might be interesting for other methodologies for risk analysis. In addition, the metamodel is generic and is therefore widely applicable on other issues beside from risk analysis, e.g. to assess the safety of structures related to time-consuming experiments depending on multiple variables.