The structural integrity of buried pipelines is threatened by the effects of Permanent Ground Deformation (PGD), resulting from seismic-induced landslides and lateral spreading due to liquefaction, requiring accurate analysis of the system performance. Analytical fragility functions allow us to estimate the likelihood of seismic damage along the pipeline, supporting design engineers and network operators in prioritizing resource allocation for mitigative or remedial measures in spatially distributed lifeline systems. To efficiently and accurately evaluate the seismic fragility of a buried operating steel pipeline under longitudinal PGD, this study develops a new analytical model, accounting for the asymmetric pipeline behavior in tension and compression under varying operational loads. This validated model is further implemented within a fragility function calculation framework based on the Monte Carlo Simulation (MCS), allowing us to efficiently assess the probability of the pipeline exceeding the performance limit states, conditioned to the PGD demand. The evaluated fragility surfaces showed that the probability of the pipeline exceeding the performance criteria increases for larger soil displacements and lengths, as well as cover depths, because of the greater mobilized soil reaction counteracting the pipeline deformation. The performed Global Sensitivity Analysis (GSA) highlighted the influence of the PGD and soil-pipeline interaction parameters, as well as the effect of the service loads on structural performance, requiring proper consideration in pipeline system modeling and design. Overall, the proposed analytical fragility function calculation framework provides a useful methodology for effectively assessing the performance of operating pipelines under longitudinal PGD, quantifying the effect of the uncertain parameters impacting system response.

This study introduces three types of multivariable fragility surfaces, integrating effective structural features to improve damage assessment. The incorporation of additional information such as building occupancies, structural responses, and underlying soil types enhances the accuracy of conventional fragility curve predictions. Additionally, three modification factors are proposed to further refine conventional fragility curves and provide more precise predictions. The multivariable fragility surfaces are developed for eccentric brace frames modeled in Opensees software which is validated by experimental results and subjected to incremental dynamic analysis with 44 far-field ground motions. The influence of soil flexibilities on structural responses is incorporated through Winkler springs, representing soil-structure interaction. Diverse occupancies, such as hospitals, museums, and residential structures, are assessed using various peak floor acceleration thresholds and story drift ratios, employing multidimensional limit state functions to consider both structural and nonstructural losses. To account for uncertainties in structural responses and a single intensity measurement, a damage-sensitive feature derived from roof acceleration response, obtained through signal processing and system identification techniques, is introduced. The results for the proposed multivariable fragility surfaces indicate that the spectral acceleration corresponding to a 50% probability of exceedance could vary between 10.2 and 89%, in comparison to the corresponding conventional fragility curves. Finally, to evaluate the application of the enhanced fragility surface and modification factors, two instrumented EBF buildings, a 4-story EBF building, and a real 5-story hospital EBF, are selected as case studies. With additional details on soil types, occupancies, and structural responses, the process of employing modification factors resulting in enhanced fragility curves is demonstrated.

The objective of this study is to explore the seismic fragility of reinforced concrete bridges, specifically in response to the vertical components of ground motions, utilizing fragility surfaces. The examination of bridge responses involves the application of optimally selected intensity measures through three-dimensional nonlinear time-history analyses, encompassing uncertainties in both superstructure materials and soil-structure interaction effects. In this investigation, an extended Probabilistic Seismic Demand Model (e-PSDM) is employed, leveraging fragility surfaces to concurrently consider vertical and horizontal excitations. The results obtained from this approach are compared with traditional fragility curves. This study emphasizes Pile-cap displacement and drift ratio as pivotal engineering damage parameters, acknowledging their sensitivity to the influences of both soil-structure interaction effects and vertical ground motion. The fragility surfaces derived from the study reveal a correlation between increased vertical spectral accelerations and elevated probabilities of surpassing both slight damage and collapse limit states. These observations underscore the critical significance and practical utility of fragility surfaces in the context of performance-based seismic assessment and design for reinforced concrete bridges. The findings from this research contribute valuable insights into the nuanced behaviour of reinforced concrete bridges under seismic conditions, emphasizing the relevance of incorporating vertical components in fragility assessments for a more comprehensive understanding of structural vulnerability.

Seismic fragility analysis is an effective method to evaluate the seismic performance of retrofitted wharf systems affected by the uncertainty of soil-cement strength. Nevertheless, fragility analysis usually consumes a large consumption of computational power. In this study, seismic fragility analysis using the artificial neural network (ANN) for the retrofitted wharf, considering the aleatory uncertainty of soil-cement strength and the epistemic uncertainty of the ANN, is carried out; On this basis, the fragility surface for two types of damage limit states considering the uncertainty of soil-cement strength is obtained. It was found that: (1) overall, the soil-cement strengthening strategy is effective for improving the seismic safety of wharf systems, however, the strengthening effect is limited, especially under strong earthquakes, will be further weakened; (2) ANN can effectively predict the maximum seismic response of retrofitted pile-supported wharves, so as to quickly carry out seismic fragility analysis. Examples show that the prediction method has good generalization; and (3) the fragility surface model considers the aleatory uncertainty of soil-cement strength and the epistemic uncertainty of the ANN, which makes the performance-based evaluation of retrofitted pile-supported wharves more comprehensive.