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Civil Engineering Association eBooks General Books Civil Engineering MSc and PhD thesis INFLUENCE OF MASONRY INFILL WALLS AND OTHER B UILDING CHARACTERISTICS ON SEIS MIC COL

INFLUENCE OF MASONRY INFILL WALLS AND OTHER B UILDING CHARACTERISTICS ON SEIS MIC COL
 TAFATNEB

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04-26-2014, 11:46 AM
INFLUENCE OF MASONRY INFILL WALLS AND OTHER B UILDING CHARACTERISTICS ON SEIS MIC COLLAPSE OF CONCRETE FRAME BUILDINGS

Author: SIAMAK SATTAR B.S ., Azad University of Najafa bad, Iran, 2004 M.S ., Mazandaran University of Science and Technology, Iran , 2007 M. S ., University of Colorado Boulder | Size: 5.2 MB | Format: PDF | Quality: Unspecified | Year: 2013 | pages: 225

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Reinforced concrete frame buildings with masonry infill walls have been built all around the world, specifically in the high seismic regions in US. Observations from past earthquakes
show that these buildings can endanger the life of their occupants and lead to significant damage and loss. Masonry infilled frames built before the development of new seismic regulations are more susceptible to collapse given an earthquake event. These vulnerable buildings are known as non-ductile concrete frames. Therefore, there is a need for a comprehensive collapse assessment of these buildings in order to limit the loss in regions with masonry infilled frame buildings.
The main component of this research involves assessing the collapse performance of masonry infilled, non-ductile, reinforced concrete frames in the Performance Based Earthquake
Engineering (PBEE) framework. To pursue this goal, this study first develops a new multi-scale modeling approach to simulate the response of masonry infilled frames up to the point of
collapse. In this approach, a macro (strut) model of the structure is developed from the response extracted from a micro (finite element) model specific to the infill and frame configuration of interest. The macro model takes advantage of the accuracy of the micro model, yet is computationally efficient for use in seismic performance assessments requiring repeated nonlinear dynamic analyses. The robustness of the proposed multi-scale modeling approach is examined through comparison with selected experimental results.


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