运营公路隧道内的火灾事件时有发生，致使衬砌结构持续劣化从而发生安全风险，为准确评估火灾后衬砌结构随运营时间增加而发生的风险事件，建立动态贝叶斯网络（DBN）模型评估火灾后运营公路隧道衬砌结构的长期安全。首先，基于火灾对隧道结构的损伤特点，构建火灾后运营公路隧道衬砌安全状态评价指标体系，获得指标权重表；
然后，采用动态贝叶斯网络建立相应的评估模型，提出火灾后衬砌安全风险等级和风险值分级，借助现场检测结果估算先验概率； 最后，根据服役寿命指数函数分布假设确定各评价指标的转移概率。广昆高速石牙山隧道火灾中心点附近衬砌表面存在大范围剥落，最大深度为40 mm，混凝土强度衰减率为0.10~0.12，将该模型用于隧道在火灾后的安全风险评估，评估结果表明，火灾后公路隧道衬砌安全的风险值随服役时间逐渐增加，35年时的风险值达到0.81，火灾诱发的混凝土劣化、衬砌裂缝会在服役过程中逐步影响隧道衬砌安全，导致安全风险随着运营时间的增加而增大。
Fire incidents in operating
highway tunnels can cause sustained deterioration of the tunnel lining
structure. To accurately predict the evolving risk associated with lining
degradation after such hazards, a dynamic Bayesian network (DBN) model is
developed to assess the long-term
structural safety of highway tunnel linings. First, based on the
characteristics of fire-induced damage, a safety
evaluation index system is established, yielding a corresponding weight table.
Then, a DBN-based evaluation model is constructed, and
the risk grades and classification values of postfire lining safety are
proposed. Prior probabilities are estimated from field detection results, while
the transfer probabilities of each evaluation index are derived assuming an
exponential distribution for tunnel service life. The model is applied to the
Shiyashan tunnel. Results show extensive concrete spalling near the center of
the fire zone, with a maximum depth of 40 mm and a concrete strength decay rate of 0.10 － 0.12. The safety risk value of the lining increases with service
time, reaching 0.81 at 35 years. The progressive deterioration of concrete and
development of cracks induced by the fire continuously impact structural
safety, resulting in a rising risk value over time.
