Lateral Capacity of URM Walls: A Parametric Study Using Macro and Micro Limit Analysis Predictions
Source abstract
Abstract
This research investigates the texture influence of masonry walls’ lateral capacity by comparing analytical predictions performed via macro and micro limit analysis. In particular, the effect of regular and quasi-periodic bond types, namely Running, Flemish, and English, is investigated. A full factorial dataset involving 81 combinations is generated by varying geometrical (panel and block aspect ratio, bond type) and mechanical (friction coefficient) parameters. Analysis of variance (ANOVA) approach is used to investigate one-way and two-way factor interactions for each parameter in order to assess how it affects the horizontal load multiplier. Macro and micro limit analysis predictions are compared, and the differences in terms of mass-proportional horizontal load multiplier and failure mechanism are critically discussed. Macro and micro limit analysis provide close results, demonstrating the reliability of such approaches. Furthermore, results underline how the panel and block aspect ratio had the most significant effect on both the mean values and scatter of results, while no significant effect could be attributed to the bond types.
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Research context
OpenAlex topics: Masonry and Concrete Structural Analysis · Building materials and conservation · Seismic Performance and Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Civil Engineering, Institute for Sustainability and Innovation in Structural Engineering, University of Minho, 4800-058 Guimarães, Portugal
School of Sustainability, Civil and Environmental Engineering, University of Surrey, Guildford GU2 7XH, UK
Department of Civil and Environmental Engineering, Carleton University, Ottawa, ON K1S 5B6, Canada
Funding
FCT/MCTES through national funds (PIDDAC) under the R&D Unit ISISE · The European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program
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