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Finite Element-Based Validation of Infill Wall Material Model for Seismic Response Analysis of Reinforced Concrete Frames Ridwan, Ridwan; Wulandari, Chrisfella; Jemaa, Yaser; Wanda Putri, T. Sy. Zahiyyah Aini; Salsabila, Elsa Attila; Yuniarto, Enno; Kamaldi, Alfian
Journal of Applied Materials and Technology Vol. 7 No. 2 (2026): March 2026
Publisher : Faculty of Engineering Universitas Riau and Applied Materials and Technology Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/Jamt.7.2.58-65

Abstract

Masonry infill walls are commonly used in reinforced concrete (RC) frame buildings for both architectural and environmental reasons.  Although many consider RC systems to be non-structural, their interaction with surrounding frames can have a significant impact on their lateral stiffness, strength, and seismic performance. This can lead to stiffness issues and soft-story failures during earthquakes. This study looks at the structural function of masonry infills. It compares the experimental load-displacement backbone curve of an infilled RC frame with numerical predictions from four well-known Equivalent Diagonal Strut (EDS) models: Holmes, Mainstone, Liau and Kwan, and Paulay and Priestley. We looked at how well the models performed for both serviceability (initial stiffness) and ultimate limit states (peak lateral strength). The findings demonstrate a definite trade-off in predictive accuracy. With a mean stiffness ratio of 1.38, the Mainstone model yielded the most accurate estimate of elastic stiffness. The Holmes and Liau and Kwan models, on the other hand, significantly overestimated stiffness (ratio = 1.92). All models were conservative (ratios < 1.0) for peak strength. Holmes and Liau and Kwan produced the closest predictions (ratio = 0.84), while Mainstone was the most conservative (ratio = 0.80). These results indicate that the best choice of EDS model depends on the design goal: Mainstone is better for serviceability assessments, while Holmes and Liau and Kwan provide more realistic predictions for ultimate lateral capacity.