.png){kind=icon}
.png){kind=icon}
Return
Evaluation of Soil-Structure Interface Models Considering Cyclic Loading Effect
.png){kind=icon}
OA
AI
DOI：10.1002/nag.3831.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The simulation of the soil-structure interface (SSI) under cyclic loading is critically important in geotechnical engineering. Numerous studies have been conducted to explore the cyclic behaviors exhibited at the SSI. However, existing model evaluations primarily rely on direct comparisons between experiments and simulations, with limited analysis focused on specific behaviors like accumulated normal displacement and stress degradation under cyclic loading. This study proposes and adapts six SSI models, including three nonlinear incremental models and three elastoplastic models. These models incorporate nonlinear shear modulus, critical state theory, and particle breakage effects to enhance their capability to capture SSI behaviors. Utilizing optimization-based calibration for a fair comparison, the model parameters are fine-tuned based on the experimental data. Comprehensive assessments including global comparisons and specific behaviors like accumulated normal displacement and stress degradation are carried out to evaluate the models' performance. The results indicate that all models effectively replicate the typical behaviors of SSI systems. By incorporating the particle breakage effect, the models can represent both the reversible and irreversible normal displacements under cyclic loading with better performance. The irreversible normal displacement remains stable and is solely influenced by the soil properties rather than the stress level. Moreover, the models successfully capture the stress degradation under constant normal stiffness caused by the irreversible normal displacement.
Keywords:
accumulated normal displacement
constitutive model
cyclic loading
soil-structure interface
stress degradation
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.6
Papers:
3.3K
Citations:
9.6K
View more organizations