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Fuzzy-logic based inelastic displacement ratios of degrading RC structures

Ozkul, S., Ayoub, A. & Altunkaynak, A. (2014). Fuzzy-logic based inelastic displacement ratios of degrading RC structures. ENGINEERING STRUCTURES, 75, pp. 590-603. doi: 10.1016/j.engstruct.2014.06.030

Abstract

The existing classical methods for estimating the inelastic displacement ratios of reinforced concrete (RC) structures subjected to seismic excitation are built upon several assumptions that ignore the effect of uncertainties on the concerning phenomenon. Uncertainty techniques are more appropriate to modeling such phenomenon that inherits impreciseness. This research presents a new method predicting the inelastic displacement ratio of moderately degrading RC structures subjected to earthquake loading using expert systems such as fuzzy logic approach.

A well-defined degrading model was used to conduct the dynamic analyses. A total of 300 earthquake motions recorded on firm sites, including recent ones from Japan and New Zealand, with magnitudes greater than 5 and peak ground acceleration (PGA) values greater than 0.08 g, were selected. These earthquake records were applied on five RC columns that were chosen among 255 tested columns based on their beam–column element parameters reported by the Pacific Earthquake Engineering Research Center (2003) [1]. A total of 96,000 dynamic analyses were conducted. The results from these analyses were used to develop the fuzzy inelastic displacement ratio model inheriting uncertainties in terms of strength reduction factor (R) and period of vibration (T). The performance evaluation of the new fuzzy logic model and four classical methods were investigated using different independent data sets. As a result, more accurate results were predicted using the new fuzzy logic model.

Publication Type: Article
Additional Information: © 2014, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Publisher Keywords: Fuzzy logic; Expert systems; Inelastic displacement ratios; Displacement estimates; Degradation
Subjects: T Technology > TJ Mechanical engineering and machinery
Departments: School of Science & Technology > Engineering
SWORD Depositor:
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