Shear Wall

Shear walls, crucial structural elements in high-rise buildings, are the focus of ongoing research aimed at improving their design and performance prediction, particularly under seismic loading. Current research emphasizes the development of accurate and interpretable machine learning models, employing techniques like Explainable Boosting Machines, Gaussian Process Regression, and Decision Trees, to predict shear wall behavior including deformation capacity, energy dissipation, and failure modes. This work is significant because it allows for faster, more reliable design optimization and risk assessment, moving beyond traditional methods that are often time-consuming and lack transparency. The resulting models offer valuable insights into the relationships between shear wall properties and performance, leading to improved building safety and resilience.