scholarly journals Application of genetic algorithm in damage detection of reinforced concrete beams using piezo ceramic transducers

2021 ◽  
Vol 1070 ◽  
pp. 012035
Author(s):  
R Mohanasundari ◽  
C Vijayaprabha
Keyword(s):  
Genetic Algorithm ◽  
Reinforced Concrete ◽  
Damage Detection ◽  
Concrete Beams ◽  
Reinforced Concrete Beams

Prediction Scheme of Torsional Strength of Reinforced Concrete Beam

2012 ◽  
Vol 214 ◽  
pp. 306-310
Author(s):  
Han Chen Huang
Keyword(s):  
Genetic Algorithm ◽  
Reinforced Concrete ◽  
Concrete Beam ◽  
Concrete Beams ◽  
Reinforced Concrete Beam ◽  
Reinforced Concrete Beams ◽  
Ann Model ◽  
Torsional Strength ◽  
Prediction Scheme ◽  
Optimal Network

This study proposes a artificial neural network with genetic algorithm (GA-ANN) for predicting the torsional strength of reinforced concrete beam. Genetic algorithm is used to the optimal network structure and parameters. A database of the torsional failure of reinforced concrete beams with a rectangular section subjected to pure torsion was obtained from existing literature for analysis. This study compare the predictions of the GA-ANN model with the ACI 318 code used for analyzing the torsional strength of reinforced concrete beam. The results show that the proposed model provides reasonable predictions of the ultimate torsional strength of reinforced concrete beams and offers superior torsion accuracy compared to that of the ACI 318-89 equation.

Damage Detection of Reinforced Concrete Beams with Novel Distributed Crack/Strain Sensors

2004 ◽  
Vol 3 (3) ◽  
pp. 225-243 ◽  
Author(s):  
Genda Chen ◽  
Huimin Mu ◽  
David Pommerenke ◽  
James L. Drewniak
Keyword(s):  
Reinforced Concrete ◽  
Damage Detection ◽  
Concrete Beams ◽  
Strain Sensors ◽  
Reinforced Concrete Beams

Strain Mode Damage Detection in Reinforced Concrete Beams Application

2012 ◽  
Vol 446-449 ◽  
pp. 566-571
Author(s):  
Jia Quan Wu ◽  
Ji Yao ◽  
Hong Yan Li ◽  
Liang Cao ◽  
Kun Ma
Keyword(s):  
Finite Element ◽  
Reinforced Concrete ◽  
Damage Detection ◽  
Structural Damage ◽  
Concrete Beams ◽  
Element Model ◽  
Reinforced Concrete Beams ◽  
Strain Mode ◽  
Finite Element Software ◽  
Injury Models

This paper describes the strain mode damage detection theory and a three-dimensional reinforced concrete beams finite element model was built by finite element software. The different degree injury models tests were compared. Experiment’s results show that the first four natural frequencies of different degree injury models are small differences while the corresponding strain modes have a significant changed in damage location. The structure of the strain mode changes are still evident when structural damage occurred in the strain mode node.

Using a Hybrid Neural Network to Predict the Torsional Strength of Reinforced Concrete Beams

2012 ◽  
Vol 538-541 ◽  
pp. 2749-2753
Author(s):  
Han Chen Huang
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Reinforced Concrete ◽  
Concrete Beams ◽  
High Strength ◽  
Activation Function ◽  
Reinforced Concrete Beams ◽  
Multilayer Perceptrons ◽  
Optimum Number ◽  
Torsional Strength

This study proposes a multilayer perceptrons neural network with genetic algorithm (GA-MLP) for predicting the torsional strength of reinforced concrete beams. Genetic algorithm is used to determine the optimum number of inputs and hidden nodes of a feedforward neural network, the optimum slope of the activation function, and the optimum values of the learning rates and momentum coefficients. A database of the torsional failure of reinforced concrete (including normal-strength and high-strength concrete) beams with a rectangular section subjected to pure torsion was obtained from existing literature for analysis. We compare the predictions of the GA-MLP model with the ACI 318 code used for analyzing the torsional strength of reinforced concrete beams. We found that the proposed model provides reasonable predictions of the ultimate torsional strength of reinforced concrete beams and offers superior torsion accuracy compared to that of the ACI 318-02 equation considering both the correlation coefficient and absolute relative error.

A simple genetic algorithm for the design of reinforced concrete beams

1997 ◽  
Vol 13 (4) ◽  
pp. 185-196 ◽  
Author(s):  
C. A. Coello Coello ◽  
A. D. Christiansen ◽  
F. Santos Hern�ndez
Keyword(s):  
Genetic Algorithm ◽  
Reinforced Concrete ◽  
Concrete Beams ◽  
Reinforced Concrete Beams ◽  
Simple Genetic Algorithm
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