Author
|
Gayan Kandethanthri
|
University
|
Concordia University, Canada |
Furthermore, the research examines the lateral performance of unbonded post-tensioned balloon-type CLT shear walls. Through traditional sensitivity analysis and machine learning models, critical parameters influencing the lateral and uplifting responses of these shear walls under lateral loading are identified. Various machine learning algorithms were applied to determine the best predictive model for these parameters. Additionally, Shapley Additive Explanations (SHAP) were used to provide deeper insights into the factors influencing the lateral and uplifting responses.
This thesis contributes valuable perspectives on integrating advanced computational techniques with traditional structural engineering practices, promoting the development of resilient and sustainable building designs.