检索结果-南通市图书馆

Computer-aided design of the effects of Cr_2O_3 nanoparticles on split tensile strength and water permeability of high strength concrete

引用

Science China(Technological Sciences) 2011年第3期54卷 663-675页

作者： Ali NAZARI Shadi RIAHI Department of Technical and Engineering Sciences Islamic Azad University Saveh Branch

In the present paper, two models based on artificial neural networks and genetic programming for predicting split tensile strength and percentage of water absorption of concretes containing Cr2O3 nanoparticles have been developed at different ages of curing. For purpose of building these models, training and testing using experimental results for 144 specimens produced with 16 different mixture proportions were conducted. The data used in the multilayer feed forward neural networks models and input variables of genetic programming models are arranged in a format of 8 input parameters that cover the cement content, nanoparticle content, aggregate type, water content, the amount of superplasticizer, the type of curing medium, age of curing and number of testing try. According to these input parameters, in the neural networks and genetic programming models the split tensile strength and percentage of water absorption values of concretes containing Cr2O3 nanoparticles were predicted. The training and testing results in the neural network and genetic programming models have shown that every two models have strong potential for predicting the split tensile strength and percentage of water absorption values of concretes containing Cr2O3 nanoparticles. It has been found that NN and GEP models will be valid within the ranges of variables. In neural networks model, as the training and testing ended when minimum error norm of network was gained, the best results were obtained and in genetic programming model, when 4 genes were selected to construct the model, the best results were acquired. Although neural network has predicted better results, genetic programming is able to predict reasonable values with a simpler method rather than neural network.

关键词： concrete curing medium Cr2O3 nanoparticles artificial neural network genetic programming split tensile strength percentage of water absorption

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Computer-aided Prediction of the ZrO_2 Nanoparticles' Effects on tensile strength and Percentage of Water Absorption of Concrete Specimens

引用

Journal of Materials Science & Technology 2012年第1期28卷 83-96页

作者： Ali Nazari Shadi Riahi Department of Materials Science and Engineering Saveh BranchIslamic Azad University

In the present paper, two models based on artificial neural networks and genetic programming for predicting split tensile strength and percentage of water absorption of concretes containing ZrO2 nanoparticles have been developed at different ages of curing. For building these models, training and testing using experimental results for 144 specimens produced with 16 different mixture proportions were conducted. The data used in the multilayer feed forward neural networks models and input variables of genetic programming models were arranged in a format of eight input parameters that cover the cement content, nanoparticle content, aggregate type, water content, the amount of superplasticizer, the type of curing medium, age of curing and number of testing try. According to these input parameters, in the neural networks and genetic programming models, the split tensile strength and percentage of water absorption values of concretes containing ZrO2 nanoparticles were predicted. The training and testing results in the neural network and genetic programming models have shown that two models have strong potential for predicting the split tensile strength and percentage of water absorption values of concretes containing ZrO2 nanoparticles. It has been found that neural network （NN） and gene expression programming （GEP） models will be valid within the ranges of variables. In neural networks model, as the training and testing ended when minimum error norm of network gained, the best results were obtained and in genetic programming model, when 4 genes were selected to construct the model, the best results were acquired. Although neural network have predicted better results, genetic programming is able to predict reasonable values with a simpler method rather than neural network.

关键词： Concrete Curing medium Zr02 nanoparticles Artificial neural network Geneticprogramming split tensile strength Percentage of water absorption

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Effects of CuO Nanoparticles on Microstructure,Physical,Mechanical and Thermal Properties of Self-Compacting Cementitious Composites

引用

Journal of Materials Science & Technology 2011年第1期27卷 81-92页

作者： Ali Nazari Shadi Riahi Department of Technical and Engineering Sciences Islamic Azad University(Saveh Branch)

In the present study,split tensile strength of self-compacting concrete with different amount of CuO nanoparticles has been *** nanoparticles with the average particle size of 15 nm were added partially to self compacting concrete and split tensile strength of the specimens has been *** results indicate that CuO nanoparticles are able to improve the split tensile strength of self compacting concrete and recover the negative effects of polycarboxylate superplasticizer on split tensile *** nanoparticle as a partial replacement of cement up to 4 wt% could accelerate C-S-H gel formation as a result of increased crystalline Ca（OH）2 amount at the early ages of *** increase of the CuO nanoparticles more than 4 wt% causes the decrease of the split tensile strength because of unsuitable dispersion of nanoparticles in the concrete *** peak appearance in conduction calorimetry tests,more weight loss in thermogravimetric analysis and more rapid appearance of related peaks to hydrated products in X-ray diffraction（XRD） results all also indicate that CuO nanoparticles up to4 wt% could improve the mechanical and physical properties of the ***,CuO nanoparticles could improve the pore structure of concrete and shift the distributed pores to harmless and few-harm pores.

关键词： Self-compacting concrete(SCC) CuO nanoparticles split tensile strength Thermogravimetric analysis(TGA) X-ray diffraction(XRD) Pore structure

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：