Steel and reinforced concrete buildings are popular structural systems. The design of these buildings is regulated by deterministic building codes. In this context, it is established that if building codes are followed, the structure will resist demands without collapsing. However, no regulation is required to control the damage of structures in terms of performance criteria. In this paper, the seismic performance and structural reliability of both steel and reinforced concrete buildings, respectively, are analyzed as a benchmark case of study. Both buildings are designed in an earthquake-prone area for two soil types, respectively. Subsequently, nonlinear dynamic analyzes are conducted and the seismic responses of the models are determined in terms of inter-story drift. To obtain seismic responses, eleven characteristic ground motions of the region are selected corresponding to three performance levels: (1) immediate occupancy, (2) life safety, and (3) collapse prevention, respectively. It was documented that the resulting maximum inter-story drift was much lower than the one obtained from modal analysis. In addition, the risk was computed in terms of reliability index integrating a novel probabilistic approach with performance-based design criteria. According to the results, a small variation in the structural risk among the buildings under consideration is observed. However, buildings designed for rigid soil proved to be more reliable. Additionally, it is observed that the buildings designed with current regulations are too conservative based on the performance criteria limits. Hence, structures located on earthquake-prone areas may be overdesigned when implementing deterministic building codes.

As the threat of natural disasters to structures intensifies, risk assessment of infrastructure has gained much importance. Fragility curves are essential tools in predicting disaster-related losses and making disaster mitigation decisions. In this paper, we propose a new method to efficiently derive accurate fragility curves for structures with high levels of nonlinearity or complexity, addressing the computational challenges of conventional finite element reliability analysis (FERA). To reduce the computational cost for calculating probability of failure in FERA, the proposed method utilizes the first-order reliability method (FORM). However, even with this approach, the computational cost of deriving the fragility curve may remain high; therefore, a surrogate model is used to further reduce costs. By training the surrogate model using the initial structural damage probabilities for a few hazard intensities, an optimal starting point can be calculated for the subsequent FORM analysis. During the fragility analysis, the surrogate model can be updated sequentially to increase the efficiency of FORM analysis continuously. In particular, the training process of the surrogate model requires no separate or additional finite element analysis because it is constructed using previous FERA results. The accuracy and efficiency of the proposed method are tested using conventional FERA and Monte Carlo simulations through a hypothetical short-column example. In addition, fragility curves are derived through a bridge flood fragility assessment considering the scour and seismic vulnerability assessment of a buried gas pipeline considering soil-structure interactions. The derived fragility curves closely match those derived using the conventional FERA, and the computational costs are reduced by 36.54 % and 52.38 %, respectively, compared with the conventional FERA, confirming its cost-effectiveness.