基于WIM数据的简支桥梁弯矩极值分布与交通特性的关系OA

Extreme traffic loads significantly challenge the safety and cost-effectiveness of highway bridges,especially under site-specific traffic conditions.Conventional assess-ments often rely on overly conservative load models,leading to excessive structural design.In this study,a framework for the prediction of maximum bending moments in simply sup-ported bridges is developed by integrating weigh-in-motion(WIM)data,traffic microsimulation,and generalized ex-treme value(GEV)regression modeling to establish rela-tionships between the GEV parameters(μ,σ,ξ)and traf-fic factors—heavy vehicle proportion,bridge span length,vehicle speed,headway,and traffic volume.Using one-year WIM data from 7.4 million vehicles,the devel-oped models for μ and σ exhibit high predictive accuracy(R²>0.95)and are validated through leave-one-out cross-validation.The prediction of ξ is less accurate(R² ≈ 0.6),requiring further improvement.Applying these mod-els to a 1 000-year return level yields a reliable,data-driven extrapolation,supporting optimized bridge design and safety assessment under varying traffic conditions.