Reliability-based optimization of nonlinear energy sink with negative stiffness and sliding friction

This paper presents implementation of a reliability-based design optimization (RBDO) for Nonlinear Energy Sink (NES) system. The RBDO is implemented with consideration of uncertainties in structural system's parameters and ground acceleration. Negative stiffness based NES and sliding friction a...

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Bibliographic Details
Published inJournal of sound and vibration Vol. 485; p. 115560
Main Authors Das, Sourav, Tesfamariam, Solomon, Chen, Yangyang, Qian, Zhichao, Tan, Ping, Zhou, Fulin
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier Ltd 27.10.2020
Elsevier Science Ltd
Subjects
Acceleration
Computing time
Design optimization
Design parameters
Energy transfer
Friction
Mathematical models
Negative stiffness
Nonlinear energy sink
Nonlinear systems
Numerical analysis
Numerical models
Optimization
Parameter uncertainty
Passive vibration control
Polynomials
Reliability
Sensitivity analysis
Shake table tests
Sliding friction
Stiffness
Uncertainty
Vibration analysis
Nonlinear energy sink
Negative stiffness
Uncertainty
Passive vibration control
Sliding friction
Optimization
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Summary:This paper presents implementation of a reliability-based design optimization (RBDO) for Nonlinear Energy Sink (NES) system. The RBDO is implemented with consideration of uncertainties in structural system's parameters and ground acceleration. Negative stiffness based NES and sliding friction are utilized to enhance passive targeted energy transfer from the primary structure to the proposed control device. For a one-story steel moment resistant frame, shake table tests were carried out to show effectiveness of the NES, and the results are used to validate numerical models. Sensitivity analysis is carried out to demonstrate the performance envelops of the proposed control strategy for different stiffness ratios and peak ground acceleration values. Reliable performance of the proposed controller, through tuning parameters of the proposed NES, are determined through the RBDO framework. To reduce computational time, polynomial-chaos-based Kriging surrogate model is used in the RBDO analysis. The numerical results demonstrate efficiency of finding optimal design parameters of the proposed NES system under uncertainties with reasonable computational effort.
ISSN:0022-460X
1095-8568
DOI:10.1016/j.jsv.2020.115560