Abstract:

To address the complexity of fire causation, the difficulty of quantifying management and human factors, and the time-dependent accumulation of risk in tobacco leaf warehousing systems, a dynamic fire risk assessment method integrating fuzzy set theory and DBN was proposed. Causation pathways and prevention barrier structures were identified based on the Bow-tie model. fuzzy set theory was introduced to map expert fuzzy judgments into DBN prior probabilities, thereby addressing the data scarcity for critical basic events. A time-dependent DBN model was then constructed to characterize the dynamic evolution of fire risk over successive management cycles. Backward diagnosis and Risk Reduction Worth (RRW) analysis were further combined to trace key hazards and prioritize mitigation actions. The results showed that, under static management conditions, the probability of the top fire event increased from 16.76% to 64.75% over 10 management cycles, while the probability of catastrophic consequences increased from 0.011% to 9.27%, exhibiting a pronounced nonlinear growth pattern. Through backward diagnosis, electrical line fault was identified as the primary physical cause with a posterior probability of 57.25%, whereas neglect of duty by fire safety personnel (49.92%) and non-compliance in hazard inspection and rectification procedures (41.38%) were determined as the dominant management-related causes. RRW analysis further revealed that the risk reduction sensitivity of management and human factors was significantly higher than that of physical factors, with neglect of duty by fire safety personnel (RRW= 1.351 2) and non-compliance in hazard inspection procedures (RRW=1.248 7) ranking first and second, respectively, indicating that strengthening personnel accountability and closed-loop hazard management yields greater risk reduction efficiency than technical upgrades alone. Physical factors provide the necessary conditions for fire occurrence; however, the cumulative effect of management deficiencies is the root cause driving the nonlinear escalation of system risk and the failure of multiple defense barriers. Dynamic risk assessment should incorporate management and human factors as core monitoring dimensions to support the formulation and implementation of differentiated risk control strategies within the dual prevention mechanism.

Key words: tobacco storage fire, risk evolution, dynamic risk assessment, fuzzy set theory, dynamic Bayesian network(DBN)