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

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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

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

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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

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Effects of Fe_2O_3 Nanoparticles on Water Permeability and Strength Assessments of High Strength Self-Compacting Concrete

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Journal of Materials Science & Technology 2012年第1期28卷 73-82页

作者： ali Khoshakhlagh ali nazari Gholamreza Khalaj Department of Materials Engineering Science and Research BranchIslamic Azad University Department of Materials Engineering Saveh BranchIslamic Azad University

In this work, compressive, flexural and split tensile strength together with coefficient of water absorption of high performance self-compacting concrete containing different amount of Fe2Os nanoparticles have been investigated. The strength and the water permeability of the specimens have been improved by adding Fe2Os nanoparticles in the cement paste up to 4.0 wt%. Fe203 nanoparticle as a foreign nucleation site could accelerate C-S-H gel formation as a result of increased crystalline Ca（OH）2 amount especially at the early age of hydration and hence increase the strength of the specimens. In addition, Fe203 nanoparticles are able to act as nanofillers and recover the pore structure of the specimens by decreasing harmful pores to improve the water permeability. Several empirical relations have been presented to predict the flexural and the split tensile strength of the specimens by means of the corresponding compressive strength at a certain age of curing. Accelerated peak appearance in conduction calorimetry tests, more weight loss in thermogravimetric analysis and more rapid appearance of peaks related to hydrated products in X-ray diffraction results indicate that Fe203 nanoparticles up to 4 wt% could improve the mechanical and the physical properties of the specimens.

关键词： Water permeability Fe203 nanoparticles Compressive strength Split tensilestrength Flexural strength

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TiO_2 nanoparticles' effects on properties of concrete using ground granulated blast furnace slag as binder

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Science China(Technological Sciences) 2011年第11期54卷 3109-3118页

作者： nazari ali RIAHI Shadi Department of Materials Science and Engineering Saveh Branch Islamic Azad University Saveh lran

In the present study,compressive strength,pore structure,thermal behavior and microstructure characteristics of concrete containing ground granulated blast furnace slag and TiO2 nanoparticles as binder were *** cement was replaced by different amounts of ground granulated blast furnace slag and the properties of concrete specimens were *** it negatively impacts the properties of concrete at early ages,ground granulated blast furnace slag up to 45 wt% was found to improve the physical and mechanical properties of concrete at later ***2 nanoparticles with the average particle size of 15 nm were partially added to concrete with the optimum content of ground granulated blast furnace slag and physical and mechanical properties of the specimens were ***2 nanoparticle as a partial replacement of cement up to 3 wt% could accelerate C-S-H gel formation as a result of increased crystalline Ca(OH)2 amount at the early age of hydration and hence increase compressive strength of *** increased TiO2 nanoparticles' content of more than 3 wt% may cause reduced compressive strength because of the decreased crystalline Ca(OH)2 content required for C-S-H gel formation and unsuitable dispersed nanoparticles in the concrete ***2 nanoparticles could improve the pore structure of concrete and shift the distributed pores to harmless and less-harm pores.

关键词：矿渣硅酸盐水泥物理机械性能纳米二氧化钛混凝土地面高炉炉渣粘结剂二氧化钛纳米粒子 Ca(OH)2

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Compressive strength and abrasion resistance of concrete containing SiO_2 and CuO nanoparticles in different curing media

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Science China(Technological Sciences) 2011年第9期54卷 2349-2357页

作者： Shadi RIAHI ali nazari Department of Materials Science and Engineering Saveh BranchIslamic Azad University

In the present study,abrasion resistance and compressive strength of concrete specimens containing SiO2 and CuO nanoparticles in different curing media have been *** cement was partially replaced by up to 2.0 wt%of SiO2 and CuO nanoparticles and the mechanical properties of the produced specimens were *** the nanoparticles content was found to increase the abrasion resistance of the specimens cured in water and saturated limewater,while this condition was not observed for compressive strength in the both curing *** enhancement of abrasion resistance was higher for the specimens containing SiO2 nanoparticles in both curing *** abrasion resistance and compressive strength of the specimens followed a similar regime as the nanoparticles increased for the specimens cured in saturated limewater,some experimental relationships has been presented to correlate these two properties of concrete for this curing *** the whole,it has been concluded that the abrasion resistance of concrete does not only depend on the corresponding compressive strength.

关键词：纳米SiO2 混凝土试件纳米粒子抗压强度耐磨性 CuO 固化媒体

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

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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：纳米Cr2O3 高强度混凝土水泥含量计算机辅助设计拉伸强度人工神经网络神经网络模型遗传规划

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Effects of Al_2O_3 nanoparticles on properties of self compacting concrete with ground granulated blast furnace slag (GGBFS) as binder

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Science China(Technological Sciences) 2011年第9期54卷 2327-2338页

作者： ali nazari Shadi RIAHI Department of Materials Science and Engineering Saveh BranchIslamic Azad University

In this work,strength assessments and percentage of water absorption of self compacting concrete containing ground granu-lated blast furnace slag (GGBFS) and Al2O3 nanoparticles as binder have been *** cement was replaced by different amounts of GGBFS and the properties of concrete specimens were *** it negatively impacts the physical and mechanical properties of concrete at early ages of curing,GGBFS was found to improve the physical and me-chanical properties of concrete up to 45 wt% at later ***2O3 nanoparticles with the average particle size of 15 nm were added partially to concrete with the optimum content of GGBFS and physical and mechanical properties of the specimens were ***2O3 nanoparticle as a partial replacement of cement up to 3.0 wt% could accelerate C-S-H gel formation as a re-sult of increased crystalline Ca(OH)2 amount at the early ages and hence increase strength and improve the resistance to water permeability of concrete *** increase of the Al2O3 nanoparticles’ content by more than 3.0 wt% would cause the reduction of the strength because of the decreased crystalline Ca(OH)2 content required for C-S-H gel *** em-pirical relationships have been presented to predict flexural and split tensile strength of the specimens by means of the corre-sponding compressive strength at a certain age of *** peak appearance in conduction calorimetry tests,more weight loss in thermogravimetric analysis and more rapid appearance of the peaks related to hydrated products in X-ray dif-fraction results,all indicate that Al2O3 nanoparticles could improve mechanical and physical properties of the concrete speci-mens.

关键词：自密实混凝土粒化高炉矿渣纳米粒子矿渣微粉力学性能混凝土地面粘结剂 Ca(OH)2

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Effect of Layers Position on Fracture Toughness of Functionally Graded Steels in Crack Divider Configuration

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Journal of Materials Science & Technology 2011年第5期27卷 443-452页

作者： ali nazari Jamshid Aghazadeh Mohandesi Shadi Riahi Department of Technical and Engineering Sciences Islamic Azad University Department of Mining and Metallurgical Engineering Amirkabir University of Technology

In the present study, fracture toughness of functionally graded steels in crack divider configuration has been modeled. By utilizing plain carbon and austenitic stainless steels slices with various thicknesses and arrangements as electroslag remelting electrodes, functionally graded steels were produced. The fracture toughness of the functionally graded steels in crack divider configuration has been found to depend on the composites＇ type together with the volume fraction and the position of the containing phases. According to the area under stress-strain curve of each layer in the functionally graded steels, a mathematical model has been presented for predicting fracture toughness of composites by using the rule of mixtures. The fracture toughness of each layer has been modified according to the position of that layer where for the edge layers, net plane stress condition was supposed and for the central layers, net plane strain condition was presumed. There is a good agreement between experimental results and those acquired from the analytical model.

关键词： Fracture toughness Modeling Functionally graded steel Crack dividerconfiguration Position of the containing phases

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Impact Energy of Functionally Graded Steels with Crack Divider Configuration

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Journal of Materials Science & Technology 2009年第6期25卷 847-852页

作者： ali nazari Jamshid Aghazadeh Mohandesi Department of Mining and Metallurgical Engineering Amirkabir University of Technology

Functionally graded steels were produced via electroslag remelting process using the primary electrodes of plain carbon and austenitic stainless steels. Charpy impact energy of as-prepared specimens was measured in the form of crack divider. The obtained results show that the impact energy of the specimens depends on the type and the volume fraction of the present phases. Based on the rule of mixtures, a mathematical model, which correlates the impact energy of functionally graded steels to the impact energy of the individual layers through Vickers microhardness of the layers, was presented. A good compatibility between the experimental results and those obtained from the model was observed.

关键词： Graded steels Impact energy Crack divider Mathematical model

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Analytical investigations and fuzzy logic-based modeling of the impact resistance of aluminum-epoxy laminated composites

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Science China(Technological Sciences) 2011年第10期54卷 2785-2794页

作者： nazari ali DIDEHVAR Neda Department of Materials Science and Engineering Saveh BranchIslamic Azad University

In the present paper, Charpy impact resistance of aluminum-epoxy laminated composites in both crack divider and crack ar-rester configurations has been investigated. In both configurations, an analytical investigation has been carried out to evaluate the effects of layers thickness on impact resistance of the specimens. A model based on fuzzy logic for predicting impact re-sistance of the specimens has been presented. For purpose of building the model, training and testing using experimental re-sults from 126 specimens produced from two basic composites were conducted. The data used for the input data in fuzzy logic models are arranged in a format of 7 input parameters that cover the thickness of layers, the number of layers, the adhesive type, the crack tip configuration, the content of SiC particles, the content of methacrylated butadiene-styrene particles and the number of test trial. According to these input parameters, in the fuzzy logic model, the impact resistance of each specimen was predicted. The training and testing results in the fuzzy logic model have shown a strong potential for predicting impact resis-tance of aluminum-epoxy laminated composites.

关键词：模糊逻辑模型层状复合材料耐冲击性环氧树脂逻辑建模层压复合材料覆盖层厚度 SiC颗粒

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