Radial basis function neural network algorithm for semi-active control of base-isolated structures

Agrahara Krishnamoorthy, Shubha Bhat, Dattatreya Bhasari

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Curved surface slider (CSS) is considered as an effective isolation device for structures subjected to earthquake ground motions. Due to constant frequency, CSS may encounter a resonance problem when subjected to near-fault earthquake ground motions. To overcome this problem, we propose CSS combined with a control device in this study. The control device consists of variable orifice fluid damper, and its damping coefficient is controlled by a radial basis function-based neural network algorithm. Numerical simulations are performed to evaluate the effectiveness of the proposed technique for only one-directional horizontal seismic excitations without any evaluation concerning the durability of CSSs. The results of the investigation demonstrate that the proposed technique is effective to reduce both the base shear and the sliding displacement of the isolated structure. In addition, the response predicted by the proposed technique is almost similar to the response of isolated structure with passive damper at optimum damping ratio.

Original languageEnglish
Article numbere1984
JournalStructural Control and Health Monitoring
Volume24
Issue number10
DOIs
Publication statusPublished - 01-10-2017

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Neural networks
Earthquakes
Damping
Orifices
Durability
Fluids
Computer simulation

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Building and Construction
  • Mechanics of Materials

Cite this

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Radial basis function neural network algorithm for semi-active control of base-isolated structures. / Krishnamoorthy, Agrahara; Bhat, Shubha; Bhasari, Dattatreya.

In: Structural Control and Health Monitoring, Vol. 24, No. 10, e1984, 01.10.2017.

Research output: Contribution to journalArticle

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