This study quantifies the seismic fragility assessment of shallow-founded buildings in liquefiable and treated soils, enhanced by drainage and densification, considering both short-and long-term behaviors. A conceptual framework is proposed for developing seismic fragility curves based on engineering demand parameters (EDPs) of buildings subjected to various earthquake magnitudes. The framework for establishing seismic fragility curves involves three essential steps. First, nonlinear dynamic analyses of soil-building systems are performed to assess both the short-term response, which occurs immediately following an earthquake, and the longterm response, when excess pore water pressure completely dissipates, and generate a dataset of building settlements. The seismic responses are compared in terms of excess pore water pressure buildup, immediate and residual ground deformation, and building settlement to explore the dynamic mechanisms of soil-building systems and evaluate the performance of enhanced drainage and densification over short-and long-term periods. Second, 38 commonly used and newly proposed intensity measures (IMs) of ground motions (GMs) are comprehensively evaluated using five statistical measures, such as correlation, efficiency, practicality, proficiency, and sufficiency, to identify optimal IMs of GMs. Third, fragility curves are developed to quantify probability of exceeding various capacity limit states, based on structural damage observed in Taiwan, for both liquefaction-induced immediate and residual settlements of buildings under different levels of IMs. Overall, this study proposes a rapid and straightforward probabilistic assessment approach for buildings in liquefiable soils, along with remedial countermeasures to enhance seismic resilience.

Selecting the optimal intensity measure (IM) is essential for accurately assessing the seismic performance of the submarine shield tunnels in the layered liquefiable seabed. However, current research relies on simplistic ranking or filtering methods that neglect the different contributions of each evaluation criterion on IM's overall performance. To address this, this study begins by developing a numerical simulation method for nonlinear dynamic analysis, considering joint deformation, ocean environmental loads, and soil liquefaction, which is validated by experimental and theoretical methods. Subsequently, a fuzzy multiple criteria decision-making (FMCDM) method based on fuzzy probabilistic seismic demand models (FPSDM) is proposed, which integrates the fuzzy analytical hierarchical process (FAHP) for calculating weights and the fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) for ranking IM alternatives. Finally, tunnel damage is classified into four states employing joint opening as the index for measuring damage, then the seismic fragility analysis is conducted. The results indicate that the optimal IM of a submarine shield tunnel situated in layered liquefiable seabed is sustained maximum velocity (SMV). Furthermore, the comparison between the fragility curves established using SMV and peak ground acceleration (PGA) reveals PGA, a frequently employed IM, notably undervaluing the seismic hazard.

Seismic risk assessment is pivotal for ensuring the reliability of prefabricated subway stations, where selecting optimal intensity measures (IMs) critically enhances probabilistic seismic demand models and fragility analysis. While peak ground acceleration (PGA) is widely adopted for above-ground structures, its suitability for underground systems remains debated due to distinct dynamic behaviors. This study identifies the most appropriate IMs for soft soil-embedded prefabricated subway stations at varying depths through nonlinear finite element modeling and develops corresponding fragility curves. A soil-structure interaction model was developed to systematically compare seismic responses of shallow-buried, medium-buried, and deep-buried stations under diverse intensities. Incremental dynamic analysis was employed to construct probabilistic demand models, while candidate IMs (PGA, PGV, and vrms) were evaluated using a multi-criteria framework assessing correlation, efficiency, practicality, and proficiency. The results demonstrate that burial depth significantly influences IM selection: PGA performs optimally for shallow depths, peak ground velocity (PGV) excels for medium depths, and root mean square velocity (vrms) proves most effective for deep-buried stations. Based on these optimized IMs, seismic fragility curves were generated, quantifying damage probability characteristics across burial conditions. The study provides a transferable IM selection methodology, advancing seismic risk assessment accuracy for prefabricated underground infrastructure. Through a systematic investigation of the correlation between IM applicability and burial depth, coupled with the development of fragility relationships, this study establishes a robust technical framework for enhancing the seismic performance of subway stations, and provides valuable insights for seismic risk assessment methodologies in underground infrastructure systems.