Nonmodel Seismic Assessment of Eccentrically Braced Steel Frames with Masonry Infills Using Machine Learning Techniques, M.Sc. Thesis Sharif University of Technology ; Mohtasham Dolatshahi, Kiarash (Supervisor)
Abstract
This study investigates the seismic behavior of eccentrically braced frames (EBFs) taking into account the influence of masonry infill walls. The primary objectives of the study are to predict the seismic global response and develop associated fragility curves using a nonmodel scenario-based machine learning framework. To model the infill walls, equivalent diagonal struts are employed, and a nonlinear pushover analysis is conducted to assess the overall impact of infills on 4- and 8-story EBF structures. An extensive database of 4 bare and 48 infilled EBFs with various infill properties is assembled to predict story-based engineering demand parameters (EDPs) containing peak and residual...
Cataloging briefNonmodel Seismic Assessment of Eccentrically Braced Steel Frames with Masonry Infills Using Machine Learning Techniques, M.Sc. Thesis Sharif University of Technology ; Mohtasham Dolatshahi, Kiarash (Supervisor)
Abstract
This study investigates the seismic behavior of eccentrically braced frames (EBFs) taking into account the influence of masonry infill walls. The primary objectives of the study are to predict the seismic global response and develop associated fragility curves using a nonmodel scenario-based machine learning framework. To model the infill walls, equivalent diagonal struts are employed, and a nonlinear pushover analysis is conducted to assess the overall impact of infills on 4- and 8-story EBF structures. An extensive database of 4 bare and 48 infilled EBFs with various infill properties is assembled to predict story-based engineering demand parameters (EDPs) containing peak and residual...
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