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Erschienen in: Neural Computing and Applications 1/2018

12.11.2016 | Original Article

Fuzzy inference system to formulate compressive strength and ultimate strain of square concrete columns wrapped with fiber-reinforced polymer

verfasst von: Kourosh Nasrollahzadeh, Ehsan Nouhi

Erschienen in: Neural Computing and Applications | Ausgabe 1/2018

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Abstract

In this paper, fuzzy inference system (FIS) is employed to develop a more accurate approach to evaluate the strength and strain capacity of axially loaded concrete columns with the square section confined by fiber-reinforced polymer (FRP) wraps. To do so, an experimental database containing 261 test data on compressive strength and 112 test data on ultimate strain is collated from the literature. By using subtractive clustering algorithm to extract cluster centers from the experimental database, the structure of FIS model is identified. To select the best FIS model, several constant and linear (i.e., zeroth- and first-order) Takagi–Sugeno FIS models with different numbers of rules are developed and their performances in terms of the model output errors with respect to training data set as well as validation data set are compared. The finally proposed FIS models for calculation of strength and strain contain as few as three rules. Besides, the proposed FIS models are expressed as closed-form formulations, which can be conveniently used in practice. The outputs of the proposed FIS models agree favorably with the test data and outperform the existing models by providing more accurate prediction of both strength and strain capacity. In view of the FIS models, a parametric study is carried out to examine the influence of various variables including the section corner radius as well as the elastic modulus and tensile strength of FRP on the capacity of FRP-confined square columns.

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Metadaten
Titel
Fuzzy inference system to formulate compressive strength and ultimate strain of square concrete columns wrapped with fiber-reinforced polymer
verfasst von
Kourosh Nasrollahzadeh
Ehsan Nouhi
Publikationsdatum
12.11.2016
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 1/2018
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-016-2658-0

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