Consequence-Oriented Fire Intensity Optimization for Structural Design under Uncertainty

Abstract

The first step in current methodologies for the (probabilistic) performance-based fire safety design and assessment of structures is characterizing fire hazard scenario(s). Next, structural response analysis is performed to estimate hazard consequences in terms of damage or loss metrics of interest. These metrics are eventually appraised to verify whether various performance objectives are achieved and design iterations are needed. Nevertheless, such approaches rely on preliminary assumptions on the structural configuration and features characterizing scenarios used as thermal inputs. Consequently, they do not fully exploit the fire–structure coupling effect, where fire affects a structure, and the characteristics of the structure also affect the combustion process and fire dynamics. Indeed, the structural design choices define the fire scenarios that could potentially affect the structural and nonstructural performance. This paper introduces a consequence-oriented fire intensity optimization (CFO) approach to the fire safety design of structures to address such limitations. The proposed approach considers fire scenarios as additional design variables and delivers them as procedure outputs, optimizing the balance between increasing structural capacity and decreasing fire intensity. Furthermore, it evaluates the effect of input uncertainties through Monte Carlo sampling. A single-span bridge subject to a car fire is used to showcase the proposed approach. For this case study, it is shown that fire scenario characteristics (fuel bed and traffic load positions, heat release rate history) maximizing consequences are strongly correlated to the structural features and cannot be set a priori. Finally, design decisions exploiting the described coupling effect to achieve various performance objectives are discussed. Overall, the proposed approach highlights the benefits of enhancing the fire and heat transfer model’s capability to capture the fire–structure coupling effect for achieving more optimized design solutions.