Owing to their distinct features, such as structural simplicity and excellent load-carrying capacity, steel truss bridges are widely applied as critical transportation networks. However, many previously designed steel truss bridges that are located in harsh environmental conditions are facing severe challenges of overloading and aging or deteriorating critical structural members due to increasing traffic load and corrosion problems (i.e., chloride-induced corrosion). As a consequence, these overloaded and deteriorated critical members may initialize localized damage (e.g., sudden member failure scenarios) and then trigger a disproportionate collapse (i.e., progressive collapse) of steel truss bridges. To this end, to protect the steel truss bridges from progressive collapse resulting from locally induced damages (e.g., sudden removal of a critical member), this paper proposed a generalized framework to identify the critical members and to qualify the alternate load path (ALP) redundancy of steel truss bridges subjected to sudden member loss of a critical member. Demand-to-capacity ratio (DCR) for linear elastic analysis and strain ratio (SR) for nonlinear dynamic analysis were employed as the design metrics and performance indicators to qualify the ALP redundancy of steel truss bridges. Effectiveness of the proposed framework in qualifying the ALP redundancy of steel truss bridges was demonstrated through the I-35W truss bridge under sudden member removal (MR) analyses. Results obtained from this study may provide beneficial information and could serve as good references for the protection of steel truss bridges that are vulnerable to sudden member loss scenarios.

The combined action of freeze–thaw cycles and chloride-induced corrosion are generally recognized as one of the main causes of the degradation of the mechanical properties and seismic performance of reinforced concrete (RC) structures in the northern frozen coastal regions. To investigate the degradation mechanisms of the seismic performance of RC columns subjected to the combined action of freeze–thaw cycles and chloride-induced corrosion, the impact of freeze–thaw cycles on the chloride diffusion coefficient of concrete was studied through concrete deterioration tests and theoretical analysis. This paper proposed a time-dependent deterioration model for RC columns, which is suitable to consider the combined action of freeze–thaw cycles and chloride-induced deterioration. The proposed deterioration model could be applied to the investigations of time-dependent seismic performance and the seismic fragility of RC columns. Based on the established deterioration model, this paper proposed a time-dependent seismic fragility analysis framework for the aging RC columns, considering the combined action of freeze–thaw cycles and chloride-induced corrosion. In addition, a representative three-span RC continuous T-shaped girder bridge that is located in the high-latitude northern frozen coastal regions of China was taken as the case study, and the time-dependent seismic fragility analysis of RC columns was conducted considering the involved uncertainties in geometric parameters, the deterioration mechanisms of the materials, and ground motions. The time-dependent seismic fragility curves of RC columns were obtained at different service time points. The results indicated that the combined action of freeze–thaw cycles and chloride-induced deterioration had a significant influence on the time-dependent seismic responses of the deteriorating RC columns. Under the combined action of freeze–thaw cycles and chloride-induced corrosion, when the RC bridge was in service for 75 years, the stirrup strength decreased by 3.88% and the cross-sectional area decreased by 30.03%. The peak stress of the confined concrete decreased by 52.1% and its peak strain increased by 12.2 times, respectively. Moreover, the time-dependent seismic fragilities of the aging RC columns under different damage states exhibited a nonlinear increase as the service life increased.

Freeze–thaw damage is one of the primary causes deteriorating the seismic resistance of reinforced concrete (RC) structures. This paper proposed a freeze–thaw damage deterioration model for C30 concrete, and it can be employed to study the time-varying seismic performance of aging RC columns. Next, this study developed a seismic fragility analysis framework for deteriorating RC columns considering the effect of freeze–thaw damage. Considering the geometric parameters of the case-study bridge, the deterioration characteristics of material, and the uncertainties involved in structural modeling and ground motions, a probabilistic seismic fragility analysis on aging RC columns was conducted. The results indicate that the influence of freeze–thaw damage cannot be ignored in studying the seismic performance of aging RC structures. The seismic fragilities of deteriorating RC columns shown a nonlinear increase trend as the increased of freeze–thaw cycles and severity of the damage state. In the early stage of freeze–thaw cycles, the seismic fragilities of RC columns increased slowly. However, the closer to the later stage of freeze–thaw cycles, the more significant of the increase in the seismic fragilities of the columns.

The numerical simulation of urban wind environments faces difficulties in capturing the turbulent characteristics due to the large computational domain. Traditional Reynolds-averaged methods (RANS) can effectively capture the average wind characteristics of urban areas. However, due to the significant dissipation and attenuation of turbulent energy in the downstream direction, this method fails to provide accurate turbulent characteristics after time-averaging processing. Therefore, in order to obtain a higher-precision turbulent wind field distribution within urban areas, this paper proposed a new numerical method named an equilibrium atmospheric boundary layer model (EABL) by modifying the control equation of the shear stress transport k–ω model. During the process, the equilibrium atmospheric boundary layer was achieved successfully, and the attenuation problem of the turbulent kinetic energy and dissipation rate during the computational fluid dynamics numerical simulation was resolved. Simultaneously, a wind tunnel experiment and six turbulence models [standard k–ε, realizable k–ε, renormalization group k–ε, large eddy simulation—narrowband synthesis random flow generator (LES-NSRFG) and LES vortex method and EABL] were employed to simulate the wind field characteristics in an actual residential area. The simulation results demonstrate that, relative to traditional RANS models, the EABL model enhances the simulation accuracy of turbulence characteristics by over two times. Furthermore, compared to LES models, the EABL model can reduce computational time by threefold.

This paper proposed a novel explainable machine learning (ML) model to predict the axial load-carrying capacity (Pmax) of FRP-confined corroded RC columns utilizing the eXtreme Gradient Boosting (XGBoost) algorithm and Shapley Additive exPlanations (SHAP) technique. The XGBoost predictive model was constructed based on thorough database of experimental tests for 285 FRP-confined corroded RC columns collected from existing studies and those performed by the authors. Twenty parameters were taken into account as critical input variables to develop the predictive model. SHAP technique was employed for performing the importance evaluation and interpreting the prediction performance of XGBoost model. Additionally, feasibility and effectiveness of the constructed XGBoost model were assessed by using several empirical design models and some other ensemble ML algorithms. The results indicated that, (i) the suggested XGBoost model was validated to be feasible to predict Pmax of FRP-confined corroded RC columns; (ii) the SHAP technique provided good explainability and interpretability to the XGBoost predictive model; (iii) the input variables could be comprehensively studied concerning the feature importance through SHAP technique, and the most important ones affecting the determination of Pmax of FRP-confined corroded RC columns were the gross sectional area of column, FRP thickness, elastic modulus of FRP, eccentricity ratio, corrosion rate, and concrete compressive strength; (iv) the prediction effectiveness and feasibility of the proposed XGBoost model were significantly superior to those of the existing empirical models and other ML algorithms, and the mean values of R2, RMSE, MAE, and MAPE of the XGBoost model were 0.978, 122 kN, 703.6 kN, and 7.7%, respectively; and (v) the recommended XGBoost model could offer the alternative approach to determine Pmax of FRP-confined corroded RC columns for design practices, in addition to the current mechanics-based design models.