Flexural Response and Parametric Analysis of Precast Concrete Composite Beams Considering New-to-Old Concrete Interface Properties

Abstract

The structural integrity of precast concrete composite beams heavily relies on the new-to-old concrete interface. Existing numerical models and traditional analytical methods struggle to capture the complex, multi-variable interfacial degradation mechanisms. This study proposes an integrated framework combining high-fidelity 3D nonlinear finite element (FE) simulations with explainable machine learning (XML). A mixed interface constitutive model, seamlessly coupling surface-based cohesive behavior with residual Coulomb friction, was established and validated to accurately replicate the full-range progressive damage and frictional slip. Using an orthogonal experimental design, a 53-sample database was generated to evaluate key design variables, including material strengths and interfacial roughness. An eXtreme Gradient Boosting (XGBoost)-based surrogate model successfully mapped the nonlinear relationships between these features and core flexural indicators, achieving an R2 exceeding 0.965. The SHapley Additive exPlanations (SHAP) framework was subsequently introduced to decode the algorithmic black box, providing transparent traceability of feature importance. Results reveal that cast-in-place concrete strength dominates initial flexural stiffness, whereas tensile reinforcement dictates yield and ultimate capacities. Crucially, interfacial roughness governs the post-peak response, enhancing energy dissipation by over 400%. This data-driven strategy validates that rationally matching material strengths with optimal interfacial friction maximizes the comprehensive flexural potential of composite members.