Application of fuzzy logic approach in predicting the lateral confinement coefficient for RC columns wrapped with CFRP

Doran, Bilge; Yetilmezsoy, Kaan; Murtazaoglu, Selim

doi:10.1016/j.engstruct.2015.01.039

Cited by 35 publications

(11 citation statements)

References 71 publications

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“…Moreover, the p-value is used as a useful statistical tool to check the significance of each of the coefficients. The variable with the larger tratio and with the smaller p-value is considered as the more significant parameter in the regression model [24,25] It is also noted that values that yield Prob(t) factors (or p-values) N 0.9 can be omitted until all remaining factors are calculated at once [24][25][26]. In the study, the significance of each coefficient was determined by Student's t-test and pvalues, which are presented in Tables 2 and 3.…”

Section: Modeling Of Degradation Of Azinphos-methyl and Chlorpyrifosmentioning

confidence: 99%

Degradation of azinphos-methyl and chlorpyrifos from aqueous solutions by ultrasound treatment

Agarwal

Tyagi

Gupta

et al. 2016

Journal of Molecular Liquids

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Section: Modeling Of Degradation Of Azinphos-methyl and Chlorpyrifosmentioning

confidence: 99%

Degradation of azinphos-methyl and chlorpyrifos from aqueous solutions by ultrasound treatment

Agarwal

Tyagi

Gupta

et al. 2016

Journal of Molecular Liquids

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“…In this study, the present fuzzy set categories were expressed in the form of letters (i.e., A, B, C, etc.) to build simple fuzzy rules, as similarly performed in the previous studies [14,38,40,44]. Therefore, the model variables had two-, eight-, ten-, or fourteen-level trapezoidal-shaped membership functions (trapmfi, where i = 1, 2, 3, …, 14) namely A, B, C, D, E, F, G, H, I, J, K, L, M and N instead of long linguistic terms such as moderately low, low, moderate, moderately high, high, very high, etc.…”

Section: Generation Membership Functions and Fuzzy Rulesmentioning

confidence: 99%

“…In the literature, the variable with the larger t-ratio and with the smaller p value is regarded as the more significant parameter in the regression model [14,15,38,40,41,47,48]. According to the absolute tratios with the smaller p values and standard errors, weld current (I) and electrode force (F e ) showed more synergistic importance than other components for the best-fit regression models in estimation of E and F k for both DC 04 and DP 600 steel sheets (Table 4).…”

Section: Prediction Of Degree Of Expulsion and Spattering Index And Wmentioning

confidence: 99%

“…Although many of classical models may give a good insight into the fundamental principles, they need to be simplified, since the mechanisms ruling a specific system may not be understood and formulated explicitly [13][14][15]. Therefore, artificial intelligence-based computational techniques have recently found a wide application in industrial and commercial control for modeling of various nonlinear system dynamics.…”

Section: Introductionmentioning

confidence: 99%

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Implementation of fuzzy logic approach to estimate the degree of expulsion and spattering index and weld strength in projection welding

Yetilmezsoy

Erhuy²,

Ateş³

et al. 2018

J Braz. Soc. Mech. Sci. Eng.

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A new Mamdani-type fuzzy inference system with four input variables such as weld current, electrode force, a transformed variable of weld time ? sheet thickness, and projection height was proposed for both DC 04 and DP 600 steel sheets to predict the degree of expulsion and spattering (conjugate) index (E) and the maximum push-out load of weld (weld strength) (F k) in projection welding. In the computational analysis, trapezoidal membership functions were constructed for the fuzzy subsets of each model variable. The product (prod) and the center of gravity (centroid) methods were implemented as the built-in AND method and defuzzification method, respectively. Fuzzy logic outputs were compared with the predictions of multiple regression analysis-based models derived within the scope of this work. Model performances were quantified by means of various statistical performance parameters. Linear regressions between the outputs of the fuzzy logic model and the experimentally measured values yielded very high determination coefficients (R 2 = 0.967-0.994). The well-correlated results reveal applicability of the fuzzy logic model for predicting the expulsion and spattering (conjugate) index, and weld strength, as well as determining the optimal combination of the process parameters to conduct the projection welding operations resulted in desired weld quality.

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“…More specifically, in the field of concrete structures strengthened with FRP systems there are examples where DM algorithms have been used to predict the lateral confinement coefficient for reinforced concrete columns wrapped with CFRP [12], the strength of FRP confined concrete cylinders [13], the shear strength of reinforced concrete beams reinforced with FRP systems using either the externally bonded (EBR) [14] or the NSM [15] techniques or even the bond strength of FRP EBR systems in concrete [16]. According to the author's best knowledge, only one work of their authorship is available where DM algorithms were applied to predict the bond strength of NSM FRP systems in concrete [17].…”

Section: Data Miningmentioning

confidence: 99%

Using data mining algorithms to predict the bond strength of NSM FRP systems in concrete

Coelho

Sena-Cruz

Neves

et al. 2016

Construction and Building Materials

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This paper presents the effectiveness of soft computing algorithms in analyzing the bond behavior of fiber reinforced polymer (FRP) systems inserted in the cover of concrete elements, commonly known as the near-surface mounted (NSM) technique. It focuses on the use of Data Mining (DM) algorithms as an alternative to the existing guidelines' models to predict the bond strength of NSM FRP systems. To ease and spread the use of DM algorithms, a web-based tool is presented. This tool was developed to allow an easy use of the DM prediction models presented in this work, where the user simply provides the values of the input variables, the same as those used by the guidelines, in order to get the predictions. The results presented herein show that the DM based models are robust and more accurate than the guidelines' models and can be considered as a relevant alternative to those analytical methods.

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Application of fuzzy logic approach in predicting the lateral confinement coefficient for RC columns wrapped with CFRP

Cited by 35 publications

References 71 publications

Degradation of azinphos-methyl and chlorpyrifos from aqueous solutions by ultrasound treatment

Degradation of azinphos-methyl and chlorpyrifos from aqueous solutions by ultrasound treatment

Implementation of fuzzy logic approach to estimate the degree of expulsion and spattering index and weld strength in projection welding

Using data mining algorithms to predict the bond strength of NSM FRP systems in concrete

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