Fire risk assessment of timber lounge bridge using fuzzy Bayesian networks

Timber lounge bridges, as important cultural heritage structures with roofed and partially enclosed corridors, are highly vulnerable to fire because of their combustible materials, intricate timber structures, and complex environments. However, fire risk assessment is challenging because of information uncertainty, limited data availability, and complex interdependencies among risk factors. To address these issues, this study establishes a fire risk assessment framework based on Fuzzy Bayesian Networks (FBN). In this framework, a hierarchical indicator system includes ignition sources, structural vulnerabilities, and emergency response capacities while explicitly modelling risk failure propagation. Prior probabilities are derived from expert judgments through triangular fuzzy numbers and similarity aggregation, and conditional relationships are quantified through the noisy-OR model. The proposed model was validated through a case study of the Liuzhai Bridge in Zhejiang Province, China. The model estimates a fire risk probability of 17% and identifies key sensitive factors and major risk failure propagation pathways. The results align well with on-site risk characteristics and demonstrate the effectiveness of the model through multi-faceted validation. This study shows that fuzzy probabilistic modelling provides a practical framework for early warning, risk prediction, and targeted mitigation strategies in timber heritage preservation.