Assessment of Masonry-Infilled Steel Frames Using Existing Experimental Tests Database in Comparison to Standards

Although the influence of infill masonry on horizontal load structure behavior is well-documented, current standards and regulations have yet to fully incorporate or explicitly define the load-bearing capacity of this complex system. Canadian and American standards present more comprehensive and specific methodologies for calculating the load-bearing capacity of infill masonry and frame systems. In contrast, European standards tend to focus on offering general guidelines for the design of these systems without delving into the detailed calculation procedures. However, extensive data and experimental studies on this topic are available in the literature. The primary aim of this paper was to compile a database of experiments involving frames with different types of infill masonry. Subsequently, the empirical results obtained through the application of analytical expressions from various standards are compared to the experimental data included in the compiled database. The obtained load-bearing values were compared to different standards and work conducted by various researchers found in the literature in order to assess their reliability. Based on the obtained results, important conclusions were drawn, specifically to the most accurate equivalent diagonal model used and the analytical expressions to be used in the assessment of the masonry-infilled steel frame behavior. The equivalent diagonal model, utilized in all analytical expressions, can provide highly accurate estimations of load-bearing capacities that closely align with the experimental results. Regardless of the type of infill element, the analytical expressions consistently overestimated the load-bearing capacity. In the presence of longitudinal force, analytical expressions tend to be conservative, providing significantly lower load-bearing values compared with experimental results, which ensures a safety margin. The database can be utilized to develop numerical models, which can subsequently serve as the foundation for probabilistic methods used in conducting reliability assessments.