Seismic fragility denotes the probabilities of a system exceeding some prescribed damage levels under a range of seismic intensities. Classical seismic fragility studies in slope engineering usually construct fragility functions by making some assumptions for fragility curve shape, and always neglect spatial variability of soil materials. In this study, an assumption-free method on the basis of probability density evolution theory (PDET) is proposed for seismic fragility assessment of slopes. The random input earthquakes and spatially-variable soil parameters in slope are simultaneously quantified. By the proposed method, assumption-free fragility curves of a slope are established without limiting the fragility curve shape. The obtained fragility results are also compared with those from two classic parametric fragility methods (linear regression and maximum likelihood estimation) and Monte Carlo simulation. The results demonstrate that the proposed assumption-free method has potential to gives more rigorous and accurate fragility results than classical parametric fragility analysis methods. With the proposed method, more reliable fragility results can be obtained for slope seismic risk assessment.

Despite the emergence of recent advancements, machine learning (ML) based methods for estimating the fragility curves of structures through probabilistic ground motion selection techniques pose a challenge due to the computational cost associated with data preparation. The primary aim of this research is to reduce the data preparation time involved in estimating the fragility curves of structures using a ground motion selection approach that considers earthquake magnitude, distance from the seismic source, and shear wave velocity of soil as essential parameters. To achieve this objective, ML algorithms are employed to calculate the fragility curves of various reinforced concrete moment resisting (RC/MR) frames with different periods, utilizing codebased and generalized conditional intensity measure (GCIM) ground motion selection methods. The SMOTE-ENN technique, a data resampling method, is used to balance the training data for the ML algorithms to address potential bias resulting from imbalanced training data. To validate the fragility curves obtained through ML, analytical fragility curves are derived for a specific structure at three damage levels and compared with the ML curves. The results demonstrate that the percentage of the enclosed area between the analytical and ML curves, relative to the area under the analytical curve, is below 10 % and 5 % for the GCIM and code-based methods, respectively. Fragility curves were generated for various structures, including regular and irregular buildings, to investigate the generalizability. Results indicate that, for the specific structures analyzed in this study, excluding torsional ones, the structure's period is a sufficient structural feature for generating fragility curves.

The traditional design criterion for buckling restrained braces (BRB) is established based on the fixed base model, which is appropriate for situations where significant soil-structure interaction (SSI) effects are absent. This paper presents a study considering the SSI effect of the 4, 6, and 8-story BRB structures with split X and Chevron V invert configurations. The study includes fragility seismic analysis, considering the SSI effects on BRB structures at different performance levels, such as immediate occupancy (IO), life safety (LS), and collapse prevention (CP). The nonlinear soil behavior is represented using the Drucker-Prager model, and the soil boundary conditions are determined based on the Leismer theory. The BRB structures are subjected to incremental dynamic analysis (IDA) using 22 far-field ground motions from FEMA P695 to create seismic fragility curves. The study findings indicate a significant rise in axial deformation of BRBs at various performance levels when the SSI effect is present. The increase in axial deformation of BRB has caused earlier damage and failure of this structure. Therefore, it is highly advisable to consider the SSI effects in the analysis and design of buckling restrained braced (BRB) structures with six stories or fewer to ensure the desired structural response during seismic events.

Seismic fragility analysis can quantitatively evaluate the seismic performance of structures from a probabilistic viewpoint and accurately characterize the relationship between the degree of structural damage and ground motion intensity. This study investigates the seismic fragility of shield tunnels in three different liquefiable and non-liquefiable soils. A plane-strain finite element model of the saturated soil and shield tunnel is established via the OpenSees computational platform employing the multi-yield surface elastoplastic PressureDependMultiYield and PressureIndependMultiYield models to simulate the constitutive behaviour of liquefiable and non-liquefiable soils. The developed model is utilized to conduct nonlinear dynamic effective stress time history analyses to generate the seismic fragility curves and surfaces based on the incremental dynamic analysis method. Meanwhile, appropriate scalar- and vector-valued intensity measures are identified based on their correlation, efficiency, practicality and proficiency. Compared with the fragility curves based on scalar-valued intensity measures, the fragility surfaces based on the vector-valued intensity measures can better describe the effect of ground motion characteristics on the structural seismic demand, and thus can more accurately assess the structural seismic performance. The seismic damage probabilities derived from the fragility curves and surfaces reveal that the seismic damage risk of the shield tunnel in sandwiched liquefiable soil deposit is higher than that of the tunnel structure located in entirely liquefiable or non-liquefiable soil profiles. This finding underscores the importance of carefully evaluating the seismic safety of shield tunnels situated in sandwiched liquefiable soil deposits.

Gas-buried steel pipes are exposed to various types of corrosion during their service life, and as a result, their initial resistance is significantly reduced. In most previous studies, the seismic vulnerability analysis of these pipes has been done without considering corrosion. The present study evaluates the seismic vulnerability of gas-buried steel pipes and extracts fragility curves considering pipe corrosion. Due to the impossibility of objectively observing the corrosion rate of pipes, a probabilistic model is presented considering the random effect in pipeline corrosion, and for different percentages of corrosion, the critical corrosion range is calculated. Then by modeling the corroded pipe in the soil and applying earthquake acceleration to it, incremental dynamic analysis (IDA) is performed in ABAQUS software and IDA curves are obtained. In the following, the probability of exceedance curves for strain are extracted, and the probability of vulnerability for different pipe corrosion conditions is determined. Finally, the seismic fragility curves of the pipeline showing the probability of failure (POF) as a function of peak ground acceleration (PGA) are obtained. The results show that corrosion percentage, variety of corrosion points, and PGA, strongly affect the uncertainty of strain data and subsequently the probability of failure of the pipeline system. For PGA = 0.4 g, in the case of a healthy pipe, the probability of exceeding the failure criterion strain is close to zero, while this probability is close to 80% for a pipe with average corrosion of 60%.