Book chapter
Load-Displacement Behavior Clustering of RC Shear Walls Using Functional Data Analysis
Dynamics of Civil Structures, Volume 2, pp 153-158
23 Oct 2021
Abstract
Reinforced concrete shear walls are one of the most common bracing systems in buildings. A significant number of existing buildings use RC shear walls designed for gravity loads and lateral loads. Several experimental studies have investigated the load-displacement behavior of these walls. As a standard approach, quasi-static cyclic loading is applied to the walls, and the load-displacement behavior (i.e. hysteresis loops) is captured. Due to the high number of points in these hysteresis loops, the comparison of the behavior of walls is complicated. This research takes advantage of functional data analysis (FDA) to analyze the hysteresis loops of walls. Functional principal component analysis (FPCA), as a dimension reduction tool, is used to reduce the dimensionality of hysteresis loops to just six dimensions. In this regard, test results of 189 different RC shear walls from 45 different research groups are used. Then, the K-means clustering method is applied to cluster the hysteresis loops based on their harmonic FPCA scores. The results show that just six dimensions are enough to represent the overall shape of hysteresis loops.
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Details
- Title
- Load-Displacement Behavior Clustering of RC Shear Walls Using Functional Data Analysis
- Creators
- Hamed Momeni - New Mexico Institute of Mining and TechnologyArvin Ebrahimkhanlou - New Mexico Institute of Mining and Technology
- Publication Details
- Dynamics of Civil Structures, Volume 2, pp 153-158
- Series
- Conference Proceedings of the Society for Experimental Mechanics Series
- Publisher
- Springer International Publishing; Cham
- Resource Type
- Book chapter
- Language
- English
- Academic Unit
- Civil, Architectural, and Environmental Engineering
- Scopus ID
- 2-s2.0-85118969219
- Other Identifier
- 991021889911804721