New models for estimating compressive strength of concrete confined with FRP sheets in circular sections

Moodi, Yaser; Mousavi, Seyed Roohollah; Sohrabi, Mahmoud Reza

doi:10.1177/0731684419858708

Cited by 11 publications

(3 citation statements)

References 77 publications

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“…Many of these models have been developed for columns with circular section (e.g. [28][29][30]), but others are also valid for square [31,32] or rectangular [33] sections.…”

Section: Introductionmentioning

confidence: 99%

Experimental investigation on the compressive behaviour of FRP-confined rectangular concrete columns

Diego

Martı́nez

Castro

et al. 2022

Archiv.Civ.Mech.Eng

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This paper presents a comprehensive experimental study on the behaviour of FRP-confined concrete in square and rectangular columns and focuses on some issues that might be addressed with a view to improving the predictive models. For this purpose, 31 prismatic concrete specimens with a height of 600 mm and low- and medium-strength concrete (20–35 MPa) were tested under centred compression. The parameters studied were the aspect ratio between the sides of the section (1, 1.5 and 2), the radius of curvature of the corners (20, 25 and 30 mm) and the number of carbon FRP layers applied. The experimental results included stress–strain curves of specimens and detailed information about the confined concrete strength and the axial and lateral strain achieved on the FRP jacket during the tests. The stress–strain response and ultimate condition are analysed, showing that FRP jacketing is an efficient technique for increasing the strength and strain capacity, but that confinement efficiency decreases as the aspect ratio of the section increases. In spite of such decrease, significant strength improvement was achieved for low-strength concrete in rectangular sections with aspect ratios of 1.5 (strength gain up to 81%), and even 2 (up to 36%). The axial strength of the tests was compared with the design criteria of four international guidelines, resulting in predictions that did not properly fit for rectangular sections. A predictive equation is proposed to assess the axial compressive strength of the FRP-confined concrete, which includes a better adjustment for the strain efficiency factor and the shape factor for rectangular columns.

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“…Many of these models have been developed for columns with circular section (e.g. [28][29][30]), but others are also valid for square [31,32] or rectangular [33] sections.…”

Section: Introductionmentioning

confidence: 99%

Experimental investigation on the compressive behaviour of FRP-confined rectangular concrete columns

Diego

Martı́nez

Castro

et al. 2022

Archiv.Civ.Mech.Eng

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“…In 2010, Sobhani et al 21 used artificial neural networks (ANN), adaptive fuzzy neural inference system (ANFIS), and regression analysis to predict the compressive strength of concrete without slump. In 2019, Moodi et al 22 proposed a modified model for determining the compressive strength of concrete confined with FRP sheets in circular sections using a genetic optimization algorithm; In their proposed models, FRP strain efficiency factor (FRP) is considered as a function of strain ratio, confinement stiffness ratio, and a combination of the two. Also in 2020, Kamgar et al 23 used a soft calculation method to estimate the compressive strength of confined concrete cylindrical specimens using a set of experimental data.…”

Section: Introductionmentioning

confidence: 99%

Prediction of compressive strength of fiber-reinforced polymers-confined cylindrical concrete using artificial intelligence methods

Jamali

Mousavi

Peyma

et al. 2022

Journal of Reinforced Plastics and Composites

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Compressive strength is the ability of materials to withstand loads without deformation or cracking. It is one of the most important criteria for evaluating the properties of concrete. The use of Fiber-Reinforced Polymers (FRP) to Strengthen concrete columns and as a supplement to improve some properties of concrete materials has received much attention in recent decades. Therefore, it is important to investigate and determine the compressive strength of confined concrete with FRP sheets. In this study, a comprehensive database containing 1066 specimens of concrete cylinders confined with FRP sheets has been collected. Then, using machine learning methods, the estimation and evaluation of the compressive strength of the mentioned specimens were discussed. The artificial neural network of multilayer perceptron (MLP) and support vector regression (SVR), fuzzy neural inference system (ANFIS), and its combination with particle swarm algorithm (PSO) and kriging interpolation method are the methods used in this study. Subsequently, these methods were compared with the models presented in previous studies. The results of this comparison show that the kriging interpolation method with a correlation coefficient of 0.985 in estimating compressive strength has the lowest error compared to other models.

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“…Different studies were conducted for estimating the compressive strength of columns wrapped by FRP. [3][4][5][6][7][8][9][10][11][12][13][14][15] Note that most of the proposed models were presented by limited specimens in the past.…”

Section: Introductionmentioning

confidence: 99%

Estimating the compressive strength of rectangular fiber reinforced polymer–confined columns using multilayer perceptron, radial basis function, and support vector regression methods

Moodi

Ghasemi

Mousavi

2021

Journal of Reinforced Plastics and Composites

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Recently, there has been a tendency to use machine learning (ML)–based methods, such as artificial neural networks (ANNs), for more accurate estimates. This paper investigates the effectiveness of three different machine learning methods including radial basis function neural network (RBNN), multi-layer perceptron (MLP), and support vector regression (SVR), for predicting the ultimate strength of square and rectangular columns confined by various FRP sheets. So far, in the previous study, several experiments have been conducted on concrete columns confined by fiber reinforced polymer (FRP) sheets with the results suggesting that the use of FRP sheets enhances the compressive strength of concrete columns effectively. Also, a wide range of experimental data (including 463 specimens) has been collected in this study for square and rectangular columns, confined by various FRP sheets. The comparison of ML-derived results with the experimental findings, which were in a very good agreement, demonstrated the ability of ML to estimate the compressive strength of concrete confined by FRP; the correlation coefficient (R2) for MLP, RBFNN, and SVR methods was equal to 0.97, 0.97, and 0.90, respectively. Similar accuracy was obtained by MLP and RBFNN, and they provided better estimates for determining the compressive strength of concrete confined by FRP. Also, the results showed that the difference between statistical indicators for training and testing specimens in the RBFNN method was greater than the MLP method, and this difference indicated the poor performance of RBFNN.

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New models for estimating compressive strength of concrete confined with FRP sheets in circular sections

Cited by 11 publications

References 77 publications

Experimental investigation on the compressive behaviour of FRP-confined rectangular concrete columns

Experimental investigation on the compressive behaviour of FRP-confined rectangular concrete columns

Prediction of compressive strength of fiber-reinforced polymers-confined cylindrical concrete using artificial intelligence methods

Estimating the compressive strength of rectangular fiber reinforced polymer–confined columns using multilayer perceptron, radial basis function, and support vector regression methods

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