Masonry walls are a cornerstone of building construction worldwide, providing both structural and non-structural functions in diverse settings. Yet, masonry’s inherent heterogeneity, arising from variations in units, mortar joints, and interfaces, presents significant challenges in accurately predicting its performance under service and extreme loads. This review focuses on two complementary perspectives: the construction aspects of various masonry wall systems (including infill, unreinforced, cavity, confined, and interlocking mortarless walls) and the finite element modeling techniques employed to capture masonry’s mechanical behavior. The review found that the wall type has a significant impact on overall structural performance and seismic response. Moreover, it is found that micro-modeling approaches (both detailed and simplified) capture localized stress and strain states in the brick–mortar interface but entail higher computational costs. Macro-modeling provides a more practical, homogenized view for large-scale analysis, treating masonry as an anisotropic continuum. Numerous researchers have demonstrated that well-calibrated models can replicate experimental load-displacement behavior in both compressive and out-of-plane (OOP) bending scenarios. In particular, advanced contact formulations have been developed to address the progressive closure of mortarless joints, while plasticitybased models are widely employed to simulate cracking and crushing in conventional masonry under seismic loading. Collectively, these studies underscore that the choice of modeling strategy depends on the level of detail required, available computational resources, and the target performance metrics. By merging robust numerical methods with proven construction practices, researchers and engineers can better predict masonry’s structural response.OPEN ACCESS Received: 10/05/2025 Accepted: 25/06/2025 Published: 14/07/2025
Published on 14/07/25
Accepted on 25/06/25
Submitted on 10/05/25
Volume 41, Issue 3, 2025
DOI: 10.23967/j.rimni.2025.10.67720
Licence: CC BY-NC-SA license
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