The primary objective of this research is to advance, through analytical and experimental research, knowledge on collapse assessment of structural systems. The focus is on sidesway collapse of frame structures, in which a specific story, or a series of stories, displaces sufficiently so that second order P-Delta effects fully offset the first order shear resistance and dynamic instability occurs. The effect of component deterioration that accelerates sidesway collapse of structural systems is of primary interest in this research.
Collapse assessment of structural systems is enhanced with the development of three extensive databases on steel and reinforced concrete beam elements. The three databases serve as the basis for validation and improvement of analytical models that explicitly model deterioration of structural components and are implemented in presently available dynamic analysis platforms. Through the calibration of several hundreds of experimental tests relationships are proposed that associate available deterioration modeling parameters with section properties and detailing criteria that control deterioration in structural components. The focus is on plastic hinge regions in steel components. These relationships and statistical measures accounting for modeling and material uncertainties serve as the basis for modeling recommendations of steel components.
Through the successful completion of earthquake-simulator collapse tests series of two scale model of a steel frame that serves as the lateral system of a 4-story office building, it is demonstrated that component deterioration has a significant effect on the collapse resistance of frame structures and that P-Δ effect can be quantified up to collapse. It is also demonstrated that it is possible to analytically predict sidesway collapse of frame structures, including the effects of component deterioration, fairly well using relatively simple models that can be incorporated in presently available dynamic analysis programs. Collapse assessment of deteriorating structural systems is enhanced with an array of case studies.
It is concluded that reliable prediction of collapse still has many hurdles to overcome, but the goal to improve the state of knowledge on how to predict the collapse capacity of deteriorating structural systems is achieved.
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