Simplified Approach for In-Plane Strength Capacity of URM Walls by Using Lower-Bound Limit Analysis and Predefined Damage Patterns
Author(s): |
Derya Karadeniz
Mustafa Tolga Yılmaz Cemal Icel Murat Altug Erberik |
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Medium: | journal article |
Language(s): | English |
Published in: | Buildings, 7 June 2022, n. 6, v. 12 |
Page(s): | 777 |
DOI: | 10.3390/buildings12060777 |
Abstract: |
In this study, a two-phase simplified approach is proposed to predict the in-plane strength capacity of unreinforced masonry (URM) walls. In the first phase, in-plane damage and failure patterns of URM walls are determined from available observational (field) data, experimental data and also from numerical analysis data. Then, a set of rules are proposed to estimate damage and failure patterns of URM wall panels. In the second phase, this valuable information is employed to develop a simplified numerical model with a coarse mesh for the masonry wall, which is consistent with the crack formation at the ultimate state. Then, lower-bound limit analysis approach is used to predict the failure load of the wall without any detailed micro-element analysis. At the final stage, the proposed approach is verified by comparing the numerical results with experimental data from URM wall tests. By the assistance of this approach, it becomes possible to estimate the lateral capacities of ordinary, non-engineered URM walls and buildings from damage patterns at failure state. As an ultimate goal, this structural information can be used for seismic risk assessment of regions where the building typology considered in this study governs the building stock. |
Copyright: | © 2022 by the authors; licensee MDPI, Basel, Switzerland. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
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data sheet - Reference-ID
10679374 - Published on:
17/06/2022 - Last updated on:
10/11/2022