International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP) (12th : 2015)

Probabilistic reliability assessment of real-time hybrid simulation of structures with degradation Ryan, Hezareigh; Chen, Cheng; Richardson, Samuel

Abstract

Improving seismic performance of structures and seismic design codes requires that laboratory experiments truthfully replicate the seismic structural response. Real-time hybrid simulation provides a viable alternative for shake table testing that allows more economical and efficient seismic performance evaluation in size-limited laboratories. Not well-understood critical parts of the structure are tested physically as experimental substructures in the laboratory, while well-behaved parts are numerically modeled by computer programs as analytical substructures. Servo-hydraulic actuators impose desired responses onto the experimental substructures. Restoring forces from substructures are integrated by a numerical algorithm to enable the replication of the entire structural response through large- or full-scale component tests. However, actuator delay causes a deviation from the exact structural response. This creates a great challenge for reliability assessment of real-time hybrid simulation results since the actual structural response is not available before or after the experiment for an immediate comparison. This paper presents a probabilistic reliability assessment approach for realtime hybrid simulation of structures with degradation. With the generalized Bouc-Wen model to emulate strength and stiffness degradation of structures close to collapse, computational simulation are conducted on single-degree-of-freedom structures subjected to selected ground motions with different intensities. Different natural frequencies are considered as well as slight, moderate and significant degradation. A lognormal distribution for critical delay corresponding to target accuracy is then established to enable probabilistic reliability assessment without actual response known a priori. Examples of applying the proposed probabilistic approach are also presented in this paper.

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Attribution-NonCommercial-NoDerivs 2.5 Canada

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