Seismic assessment of unreinforced masonry façades from images using macroelement-based modeling.

Mayar Ariss, Bryan German Pantoja-Rosero, Fabio Duarte, Mikita Klimenka, Carlo Ratti
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Abstract

Despite the variability of urban infrastructure, unreinforced masonry buildings remain globally prevalent. Constructed from brick, hollow concrete blocks, stone, or other masonry materials, these structures account for a significant proportion of fatalities during seismic events-particularly in regions with limited access to early warning systems. Due to the complex behavior of masonry, accurately assessing structural vulnerabilities is highly dependent on the chosen modeling strategy. Yet, scalable, cost-effective approaches based on simple RGB imagery can still offer valuable insights. In this context, building on a previously developed digitalization methodology, this study proposes an automated, image-based framework for the rapid, non-invasive seismic evaluation of façades, addressing important research gaps in disaster resilience. The framework links image data with structural simulation by extracting visual and geometric features and translating them into consistent macroelement models using computer vision techniques, enabling nonlinear analyses under in-plane cyclic loading. The adopted numerical strategy has been extensively validated in prior work, with predictions closely aligning with experimental results. While the outcomes are predictive rather than diagnostic, future integration with publicly accessible urban imagery may enable the development of real-time, cross-border seismic risk maps.

利用基于宏单元的建模方法从图像中对未加筋砌体立面进行地震评估。
尽管城市基础设施千差万别,但未加固的砖石建筑仍然在全球普遍存在。这些建筑物由砖、空心混凝土块、石头或其他砌筑材料建造而成,在地震事件中造成的死亡人数占很大比例,特别是在早期预警系统有限的地区。由于砌体的复杂行为,准确评估结构脆弱性高度依赖于所选择的建模策略。然而,基于简单RGB图像的可扩展、经济有效的方法仍然可以提供有价值的见解。在此背景下,本研究在先前开发的数字化方法的基础上,提出了一个自动化的、基于图像的框架,用于快速、非侵入性的地震评估,解决了灾害恢复能力方面的重要研究空白。该框架通过提取视觉和几何特征并使用计算机视觉技术将其转换为一致的宏元素模型,将图像数据与结构模拟联系起来,从而实现平面内循环载荷下的非线性分析。所采用的数值策略在先前的工作中得到了广泛的验证,预测与实验结果密切一致。虽然结果是预测性的,而不是诊断性的,但未来与可公开访问的城市图像的整合可能使实时的跨境地震风险地图的开发成为可能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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