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Experimental testing of decoupled masonry infills with steel anchors for out-of-plane support under combined in-plane and out-of-plane seismic loading
(Construction and Building Materials, 2022)
Because of simple construction process, high energy efficiency, significant fire resistance and excellent sound isolation, masonry infilled reinforced concrete (RC) frame structures are very popular in most of the countries ...
Seismic performance of an industrial multi-storey frame structure with process equipment subjected to shake table testing
(Engineering Structures, 2021)
Past earthquakes demonstrated the high vulnerability of industrial facilities equipped with complex process technologies leading to serious damage of process equipment and multiple and simultaneous release of hazardous ...
Influence of slab deflection on the out-of-plane capacity of unreinforced masonry partition walls
(Engineering Structures, 2023)
Severe damage of non-structural elements is noticed in previous earthquakes, causing high economic losses and posing a life threat for the people. Masonry partition walls are one of the most commonly used non-structural ...
Experimental results of reinforced concrete frames with masonry infills with and without openings under combined quasi‑static in‑plane and out‑of‑plane seismic loading
(Bulletin of Earthquake Engineering, 2023)
Reinforced concrete (RC) frames with masonry infills can be encountered all over the world, especially in earthquake prone regions. Although masonry infills are usually not considered in the design process, in the case of ...
Numerical Modeling of Two Adjacent Interacting URM Structures
(IPSI, Belgrade, 2024)
Masonry structures in addition to their long heritage are still widely used in civil engineering practice. It should be emphasized that a lot of research has already been done on the seismic behavior of masonry structures. ...
Rapid earthquake loss assessment based on machine learning and representative sampling
(Earthquake Spectra, 2021)
This paper proposes a new framework for rapid earthquake loss assessment based on a machine learning damage classification model and a representative sampling algorithm. A Random Forest classification model predicts a ...