Response surface modelling in quantitative risk analysis for life safety in case of fire

This paper proposes part of a framework for the development of a risk assessment methodology to quantify the life safety risk of building occupants in the context of fire safety design. An important aspect of quantitative risk analysis (QRA) concerns taking into account the variability of the design parameters. In QRA for life safety in case of fire, one of the key research challenges to take probability into account is the complexity of the different submodels. Another key aspect is the high computational time for performing a set of simulations. In order to tackle these problems, a response surface model (RSM) for sub-models, which support the global QRA method, is useful. In this paper, this is illustrated in particular for the modelling of smoke spread. More specifically, the focus is on the development of a method and a model for estimating the RSM using a Least Squares (LS) technique or the Polynomial Chaos Expansion (PCE) approach. Both methods were found to be suitable for the intended purpose, but PCE provides the best fitting response surface model based on the obtained data for the case at hand. The model is tested in a practical case study with Computational Fluid Dynamics (CFD) incorporating the Fire Dynamics Simulator (FDS) model