Evaluation of seismic collapse risk in structures using power and dynamical systems theory based approach

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Embargoed until 2021-01-01
Copyright: Pathak, Shivang
Under the performance based earthquake engineering (PBEE) philosophy, the design of structures to resist collapse requires meeting a target level of collapse prevention. Therefore, the quantification of the collapse capacity of a structure is regarded as an essential step to develop robust designs that can ensure safety under extreme earthquake scenarios. Although, in the recent two decades, tremendous progress has been achieved in the field of computational analysis of deteriorating structures, the accurate prediction of collapse capacity remains a topical issue because current methods used for predicting collapse do not correlate to the exact occurrence of dynamic instability in the structure. In the present study, a new physics-based collapse criterion is proposed. It uses power (energy-rates) to predict seismic collapse capacity of structures. The development of the criterion stems from the principles of Lyapunov stability and dissipative dynamical systems. A series of validated collapse simulation models are developed to illustrate the applicability of this criterion to both vertical gravity load and sidesway collapse mechanisms. Furthermore, a dynamical systems theory algorithm is developed to identify the exact occurrence of dynamic instability. The developed power-based collapse criterion is then optimised by comparing its collapse predictions to those derived from the dynamical systems theory algorithm. Finally, the refined power-criterion is then used to evaluate the collapse risk in realistic RC frame buildings designed to meet existing codes’ requirements. The collapse risk estimates are compared to those derived from the existing techniques. It was found that the proposed criterion can serve as a leading indicator of collapse and can potentially result in economic and safe designs.
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Pathak, Shivang
Khennane, Amar
Al-Deen, Safat
Watt, Simon
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PhD Doctorate
UNSW Faculty
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