Societal decision-making for optimal fire safety

Fire safety measures save lives and reduce economic losses caused by building fires. However, these benefits come at a cost, because fire safety is not free of charge. An economic optimum is achieved when the total costs of fire and fire safety are minimized. Of course, fire safety decisions cannot be based only on economic reasoning. The safety of building occupants is an important boundary condition for monetary optimization. Societal resources for life saving measures are limited and should be invested where the largest risk reduction can be achieved. Thus, also the definition of acceptance criteria for decisions regarding investments into life safety should be based on efficiency considerations. The focus of this thesis is on the optimization of societal investments for preventive building fire safety. The starting point is the formulation of a general decision problem consisting of two parts: monetary optimization and societal risk acceptance. The optimization may be performed either by a private decision-maker or at societal level. The acceptability of fire safety decisions with respect to life safety, on the other hand, is always evaluated from a societal point of view. Quantitative acceptance criteria can be derived based on the marginal life saving costs principle, which ensures that societal resources are directed to the most efficient risk reduction measures available. Decisions on fire safety measures are generally made by the owner of a building. At societal level, investments into building fire safety are controlled mainly based on codes and regulations. The owner is free to optimize fire safety using his own objective function, provided that he fulfils the minimum requirements defined by the code. Traditionally, fire safety is regulated based on prescriptive rules defining in detail which measures have to be taken to reduce fire risk. In order to increase the flexibility of code-based fire safety design, a number of countries around the world have adopted performance-based codes, which specify the design objectives, but leave the concrete choice of measures to the designers. Unfortunately, the code objectives are rarely formulated in quantitative terms. In this thesis it is shown how quantitative safety goals for code-based design may be derived from a generic risk-informed framework for balancing the costs and benefits of fire safety. Following this approach, both prescriptive and performance-based fire safety codes can be based on the same principles of monetary optimization and acceptable life safety. Fire safety decisions are decisions under uncertainty. Optimizing fire safety thus requires risk assessment for evaluating the effect of safety investments on the expected monetary and human consequences of fire. For a comparison between the uncertain benefits of fire safety measures and their costs, the risk has to be assessed in absolute terms, with as little bias as possible. The present thesis explores the use of statistical data to reduce the modelling bias resulting from assumptions and simplifications used to estimate the risk. A framework for the calibration of engineering fire risk models with data collected by, for instance, fire brigades or insurance companies is developed. The proposed approach allows a combination of engineering knowledge with observations from real fire events, making the best use of both sources of information.