Application of Neural Network for Concrete Carbonation

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Application of Neural Network for Concrete Carbonation ...

APPLICAtION Of NeUrAL NetWOrK fOr CONCrete CArbONAtION DePth PreDICtION 67 sensitivity, and is used to predict carbonation depth of concrete, and reasonable results are obtained. 2.1 Standard PSO algorithm The speed–location search model is adopted in the standard PSO algorithm (Kennedy, Eberhart et al., 1995; Li et al., 2005).

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Application of Neural Network for Concrete Carbonation ...

Concrete carbonation is one of the most significant causes of deterioration of reinforced concrete structures in atmospheric environment. However, current models based on the laboratory tests cannot predict carbonation depth accurately. In this paper, the BP neural network is optimized by the particle swarm optimization (PSO) algorithm to establish the model of the length of the partial ...

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Application of Neural Network for Concrete Carbonation ...

The prediction of concrete carbonation by neural networks has been of interest for some time [26][27][28] [29] [30][31][32][33], but no one has yet estimated the lifetime of concrete containing ...

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Application of Neural Network for Concrete Carbonation ...

Application of Neural Network for Concrete Carbonation Depth Prediction . By Daming Luo, Ditao Niu and Zhenping Dong. Cite . BibTex; Full citation; Publisher: Purdue University Libraries Scholarly Publishing Services. Year: 2014. DOI identifier: 10.5703/1288284315384. OAI identifier: Provided by:

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Application of Neural Network for Concrete Carbonation ...

Application of Neural Network for Concrete Carbonation Depth Prediction . By Daming Luo, Ditao Niu and Zhenping Dong. Cite . BibTex; Full citation; Publisher: Purdue University Libraries Scholarly Publishing Services. Year: 2014. DOI identifier: 10.5703/1288284315384. OAI identifier: Provided by:

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Analysis of carbonation behavior in concrete using neural ...

01-01-2010  For applying the result of neural network to system dynamics, D CO 2 neural is considered in the flux term with changing effect on porosity. Based on framework of FEM program DUCOM developed by the University of Tokyo , , a computational scheme of carbonation modeling with neural network and changing porosity is set up as shown in Fig. 8.

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Artificial neural network analysis of concrete carbonation ...

24-10-2010  Abstract: Two artificial neural networks (ANN), backpropagation neural network (BPNN) and the radial basis function neural network (RBFNN), are proposed to predict the carbonation depth of stressed concrete. In order to generate the training and testing data for the ANNs, an accelerated carbonation experiment was carried out for stressed concrete specimens.

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Research and application on neural network in concrete ...

Author(s): GAO Panxiang, YU Junqi, NIU Ditao, DONG Zhenping, LUO Daming Pages: 238-241,250 Year: 2014 Issue: 14 Journal: Computer Engineering and Applications Keyword: neural network; concrete; carbonation depth; structural durability; Abstract: For the defects on search speed slow and ease into the local minima of the BP neural network, the model about each factor and the length of

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Research and application on neural network in concrete ...

Research and application on neural network in concrete carbonation depth prediction: GAO Panxiang1, YU Junqi1, NIU Ditao2, DONG Zhenping2, LUO Daming2: 1.School of Information and Control Engineering, Xi’an University of Architecture and Technology, Xi’an 710055, China

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Research and application on neural network in concrete ...

For the defects on search speed slow and ease into the local minima of the BP neural network, the model about each factor and the length of the partial carbonation zone is established, which uses the PSO algorithm to optimize the BP neural network. Based on the experimental simulation training, the improved model is applied to the part location of a concrete bridge on carbonation depth ...

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Calis Application of an artificial neural network for ...

Lee S, Lee C (2014). Prediction of shear strength of FRP-reinforced concrete flexural members without stirrups using artificial neural networks. Engineering Structures, 61, 99–112. Lenard MJ, Alam P, Madey GR (1995). The Application of Neural Networks and a Qualitative Response Model to the Auditor’s Going Concern Uncertainty Decision.

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Neural Network Modeling of Concrete Carbonation

The American Concrete Institute. Founded in 1904 and headquartered in Farmington Hills, Michigan, USA, the American Concrete Institute is a leading authority and resource worldwide for the development, dissemination, and adoption of its consensus-based standards, technical resources, educational programs, and proven expertise for individuals and organizations involved in concrete design ...

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CaPrM: Carbonation prediction model for reinforced ...

15-12-2015  In another perspective, most of the existing neural network based carbonation prediction models do not employ all the necessary parameters that influence the microstructural properties of concrete. The common parameters utilized in most of the available models are composition and amount of cement and water to cement ratio (w/c) to describe the concrete properties.

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(PDF) A neural network method for analysing concrete ...

Magazine of Concrete Research, 2008, 60, No. 7, September, 475–486 doi: 10.1680/macr.2007.00016 A neural network method for analysing concrete durability N. Ukrainczyk* and V. Ukrainczyk† University of Zagreb; ‘Mostprojekt’ d.o.o This paper describes the use of an artificial neural network (ANN) method for the analysis of relationships between a number of input parameters and observed ...

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Artificial neural network analysis of concrete carbonation ...

24-10-2010  Abstract: Two artificial neural networks (ANN), backpropagation neural network (BPNN) and the radial basis function neural network (RBFNN), are proposed to predict the carbonation depth of stressed concrete. In order to generate the training and testing data for the ANNs, an accelerated carbonation experiment was carried out for stressed concrete specimens.

Get price

Research and application on neural network in concrete ...

Research and application on neural network in concrete carbonation depth prediction: GAO Panxiang1, YU Junqi1, NIU Ditao2, DONG Zhenping2, LUO Daming2: 1.School of Information and Control Engineering, Xi’an University of Architecture and Technology, Xi’an 710055, China

Get price

Research and application on neural network in concrete ...

Author(s): GAO Panxiang, YU Junqi, NIU Ditao, DONG Zhenping, LUO Daming Pages: 238-241,250 Year: 2014 Issue: 14 Journal: Computer Engineering and Applications Keyword: neural network; concrete; carbonation depth; structural durability; Abstract: For the defects on search speed slow and ease into the local minima of the BP neural network, the model about each factor and the length of

Get price

Research and application on neural network in concrete ...

For the defects on search speed slow and ease into the local minima of the BP neural network, the model about each factor and the length of the partial carbonation zone is established, which uses the PSO algorithm to optimize the BP neural network. Based on the experimental simulation training, the improved model is applied to the part location of a concrete bridge on carbonation depth ...

Get price

Optimized neural network based carbonation prediction model

Keywords: concrete carbonation, carbonation prediction, modelling, neural network 1. Introduction Carbonation of concrete is one of the major causes of deterioration in reinforced concrete structures [1, 2]. It is a natural physicochemical process caused by the penetration of carbon

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Neural Network Modeling of Concrete Carbonation

The American Concrete Institute. Founded in 1904 and headquartered in Farmington Hills, Michigan, USA, the American Concrete Institute is a leading authority and resource worldwide for the development, dissemination, and adoption of its consensus-based standards, technical resources, educational programs, and proven expertise for individuals and organizations involved in concrete design ...

Get price

Calis Application of an artificial neural network for ...

Lee S, Lee C (2014). Prediction of shear strength of FRP-reinforced concrete flexural members without stirrups using artificial neural networks. Engineering Structures, 61, 99–112. Lenard MJ, Alam P, Madey GR (1995). The Application of Neural Networks and a Qualitative Response Model to the Auditor’s Going Concern Uncertainty Decision.

Get price

Application of Neural Networks for Estimation of Concrete ...

This study presents the first effort in applying neural network-based system identification techniques to predict the compressive strength of concrete based on concrete mix proportions. Back-propagation neural networks were developed, trained, and tested using actual data sets of concrete mix proportions provided by two ready-mixed concrete companies.

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An analytical study on the prediction of carbonation ...

Y. Liu, S. Zhao and C. Yi, The forecast of carbonation depth of concrete based on RBF neural network. 2008 Second International Symposium on Intelligent Information Technology Application. IEEE. 3 (2008), pp. 544-548.

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(PDF) A neural network method for analysing concrete ...

Magazine of Concrete Research, 2008, 60, No. 7, September, 475–486 doi: 10.1680/macr.2007.00016 A neural network method for analysing concrete durability N. Ukrainczyk* and V. Ukrainczyk† University of Zagreb; ‘Mostprojekt’ d.o.o This paper describes the use of an artificial neural network (ANN) method for the analysis of relationships between a number of input parameters and observed ...

Get price
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