Machine learning-enhanced fragility curves: Advancing reliability and safety of structures in seismic risk assessment

Seismic performance and vulnerability assessment of rockfill dams on liquefiable ground with gravel berms for liquefaction mitigation

Seismic failure assessment of a 19th-Century masonry minaret with and without iron clamp and dowel Retrofit: Experimental Testing, ambient vibration validation and numerical modeling

Seismic resilience assessment of deteriorating riverine bridges incorporating historical climatic data

Seismic behavior and damage assessment of steel reinforced lightweight aggregate concrete columns

Seismic performance and damage assessment of CFST latticed column-composite box girder joints

Seismic repair assessment of welded beam-to-box column connections in high-rise steel buildings

Data-driven multi-criteria framework for the seismic and post-earthquake performance assessment of corroded RC bridge piers

Seismic performance assessment of post-tensioned ultra-high performance concrete prefabricated retaining blocks based on OpenSees

Seismic resilience-based assessment and design of concrete bridge piers reinforced with shape memory alloy bars

Seismic fragility assessment of structures with friction pendulum isolators, tuned mass dampers, and hybrid control systems

Seismic performance and fragility assessment of BRBFs subjected to sequential earthquakes

Seismic damage assessment of reinforced concrete frame structures based on transfer-residual networks

Seismic vulnerability assessment of reinforced concrete frames with various masonry infill patterns

Laboratory validation of seismic damage assessment in reinforced soil models based on sensor-enabled piezoelectric geogrids (SPGG)

Stacked machine learning-based probabilistic seismic demand and risk assessment of railway embankments with variable slopes

Seismic performance and resilience assessment of an innovative self-centering modular disc spring device

SMOTE-enhanced XGBoost for rapid seismic damage assessment of bridge portfolios

A fast seismic assessment technique for reinforced concrete buildings: Machine learning-based Hassan Index

Accurate seismic safety assessment of nuclear power plant (NPP) structures with pile foundations on soft soil sites requires consideration of soil nonlinearity and pile–soil–structure interaction (PSSI). This study develops an efficient partitioned SSI framework, where the nonlinear soil response is simulated using the Davidenkov skeleton curve combined with a modified Masing rule and solved by an explicit time integration scheme, while the structural dynamics are evaluated using the modal superposition method. The framework is applied to a pile-supported CAP1400 NPP model on deep soft soil, with both piles and the superstructure modeled as elastic. Two computational schemes are examined: (a) explicit integration of the soil while treating the piles and structure as an integrated system analyzed via modal superposition; and (b) explicit integration of both soil and piles, with the structure analyzed using modal superposition. Under pulse excitation, both schemes yield comparable dynamic responses, whereas scheme (b) improves computational efficiency by over threefold (88 h vs. 293 h). Results using scheme (b) under RG1.60 excitation show that soil nonlinearity reduces and delays structural responses but increases pile bending moments and stress concentration, demonstrating the framework’s effectiveness and practicality for nonlinear SSI analysis of NPP structures.