RESPONSE VARIABILITY WITH RANDOM UNCERTAINTY IN A TUNED LIQUID COLUMN DAMPER

Authors

  • Mansour H. Alkmim University of Brasilia
  • Adriano T. Fabro
  • Marcus V. G. de Morais

DOI:

https://doi.org/10.26512/ripe.v2i16.21611

Keywords:

Tuned Liquid Column Damper. Vibration Absorber. Model Uncertainty. Stochastic Analysis.

Abstract

Passive energy dissipation systems encompass a range of materials and devices for enhancing damping. They can be used both for natural hazard mitigation and for rehabilitation of aging or deficient structures. Among the current passive energy dissipation systems, tuned liquid column damper (TLCD), a class of passive control that utilizes liquid in a “U” shape reservoir to control structural vibration of the primary system, has been widely researched. Uncertainties can arise from simplifications in the model and from nonlinearities. To quantify uncertainties, random variables need to be associated with the systems parameters, such as stiffness and damping ratio, along with their probability density function. The Maximum Entropy Principle is used to construct the probability density function since it avoids using misinformation in the construction of model. In this paper the frequency response function of a system with a TLCD is investigated considering two cases of parameter uncertainty: the first considering uncertainties only in one parameter, the absorber damping ratio and the second considering uncertainties in two parameters, the absorber damping ratio and the structure stiffness. The results showed that, for the first case, the uncertainty is only predominant near the resonance and anti-resonance region and can indeed interfere in the optimum condition of the absorber. For the second case, the uncertainties are presented in all frequencies.

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Published

2017-01-30

How to Cite

H. Alkmim, M., T. Fabro, A., & V. G. de Morais, M. (2017). RESPONSE VARIABILITY WITH RANDOM UNCERTAINTY IN A TUNED LIQUID COLUMN DAMPER. Revista Interdisciplinar De Pesquisa Em Engenharia, 2(16), 1–11. https://doi.org/10.26512/ripe.v2i16.21611

Issue

Vol. 2 No. 16 (2016): STOCHASTIC MODELING AND UNCERTAINTY QUANTIFICATION

Section

Artigos

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