Different testing methods for assessing the synthetic fiber distribution in cement-based composites

Cao, Mingcui; Mao, Yaqian; Khan, Mehran; Wen, Shi Wu; Shen, Shirley

doi:10.1016/j.conbuildmat.2018.06.207

Cited by 55 publications

(34 citation statements)

References 45 publications

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“…[1][2][3][4][5][6]. Currently, the main reinforcing materials of fiber-reinforced cementbased composite materials are steel fiber, polypropylene fiber, polyvinyl alcohol (PVA) fiber, carbon fiber, glass fiber, basalt fiber, and cellulose fiber [7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Mechanical Properties of SiO₂‐Coated Carbon Fiber‐Reinforced Mortar Composites with Different Fiber Lengths and Fiber Volume Fractions

Heo

Park

Song

et al. 2020

Advances in Civil Engineering

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In the present study, SiO2 particles were coated on the surface of carbon fibers by means of chemical reaction of silane coupling agent (glycidoxypropyl trimethoxysilane, GPTMS) and colloidal SiO2 sol to improve the interfacial bonding force between fibers and matrix in cement matrix. The surface of the modified carbon fibers was confirmed through a scanning electron microscope (SEM). The mechanical properties of SiO2-coated carbon fiber mortar and uncoated carbon fiber mortar with different fiber lengths (6 mm and 12 mm) and fiber volume fractions (0.5%, 1.0%, 1.5%, and 2.0%) were compared and analyzed. The experimental results show that the flow values of the carbon fiber mortar were greatly disadvantageous in terms of fluidity due to the nonhydrophilicity of fibers and fiber balls, and the unit weight decreased significantly as the fiber volume fractions increased. However, the air content increased more or less. In addition, regardless of whether the fibers were coated, the compressive strength of carbon fiber-reinforced mortar (CFRM) composite specimens tended to gradually decrease as the fiber volume fractions increased. On the other hand, in case of the SiO2-coated CFRM composite specimens, the flexural strength was significantly increased compared to uncoated CFRM composite specimens and plain mortar specimens, and the highest flexural strength was obtained at 12 mm and 1.5%, particularly. It can be seen that the new carbon fiber surface modification method employed in this study was very effective in enhancing the flexural strength as cement-reinforcing materials.

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Section: Introductionmentioning

confidence: 99%

Mechanical Properties of SiO₂‐Coated Carbon Fiber‐Reinforced Mortar Composites with Different Fiber Lengths and Fiber Volume Fractions

Heo

Park

Song

et al. 2020

Advances in Civil Engineering

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“…It is used in the production of additives for cement mortars, industrial concrete, insulation materials, ceramic products, products with an increased resistance to high temperature and high-performance self-compacting concrete [ 29 ]. It has been reported that industrial waste and numerous artificial and natural fibers can be successfully utilized to enhance the properties of concrete [ 30 , 31 , 32 ]. Ganesh et al [ 33 ] research was based on the high-performance fiber-reinforced geopolymer concrete.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Geopolymer Concrete Compressive Strength Using Novel Machine Learning Algorithms

Ahmad

Chaiyasarn

et al. 2021

Polymers

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The innovation of geopolymer concrete (GPC) plays a vital role not only in reducing the environmental threat but also as an exceptional material for sustainable development. The application of supervised machine learning (ML) algorithms to forecast the mechanical properties of concrete also has a significant role in developing the innovative environment in the field of civil engineering. This study was based on the use of the artificial neural network (ANN), boosting, and AdaBoost ML approaches, based on the python coding to predict the compressive strength (CS) of high calcium fly-ash-based GPC. The performance comparison of both the employed techniques in terms of prediction reveals that the ensemble ML approaches, AdaBoost, and boosting were more effective than the individual ML technique (ANN). The boosting indicates the highest value of R2 equals 0.96, and AdaBoost gives 0.93, while the ANN model was less accurate, indicating the coefficient of determination value equals 0.87. The lesser values of the errors, MAE, MSE, and RMSE of the boosting technique give 1.69 MPa, 4.16 MPa, and 2.04 MPa, respectively, indicating the high accuracy of the boosting algorithm. However, the statistical check of the errors (MAE, MSE, RMSE) and k-fold cross-validation method confirms the high precision of the boosting technique. In addition, the sensitivity analysis was also introduced to evaluate the contribution level of the input parameters towards the prediction of CS of GPC. The better accuracy can be achieved by incorporating other ensemble ML techniques such as AdaBoost, bagging, and gradient boosting.

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“…As for the direct test method, digital image processing technology (DIPT) has been widely applied for the fiber reinforced composites in recent years [ 23 , 24 ]. Cao et al [ 25 ] determined the relationship between the fiber distribution and properties of fiber-reinforced cement-based composites (FRCs) by using DIPT. Lataste et al [ 26 ] used DIPT to characterize the distribution of steel fibers in concrete with superhigh fiber contents and proposed the concept of “intensity of orientation of fibers”.…”

Section: Introductionmentioning

confidence: 99%

Quantitative Evaluation of Carbon Fiber Dispersion in Amorphous Calcium Silicate Hydrate-Based Contact-Hardening Composites

Xiong

Peng

et al. 2021

Molecules

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Carbon fiber dispersion has a substantial influence on the properties of amorphous calcium silicate hydrate-based contact-hardening composites. In this study, a mixture of carbon fiber and calcium silicate hydrate powder was compressed into solid composites at 40 MPa for one minute. The mechanical properties and electrical resistivity of the solid materials were measured, and the dispersion of carbon fibers was quantitatively evaluated by digital image processing technology. The Taipalu model was used to build the correlation between the electrical resistivity of the composites and the carbon fiber dispersion. The results of the electrical resistivity showed that the down threshold of carbon fiber content in the contact-hardening composites was 1.0 wt.% and the electrical resistivity was 30,000 Ω·cm. As the fiber content increased to 2.0 wt.%, the electrical resistivity dropped to 2550 Ω·cm, which was attributed to the increase in fiber dispersion uniformity in the solid composites, and the value of the fiber distribution coefficient reached a maximum value of 0.743. A subsequent decrease in the uniformity of the fiber dispersion was observed at a high fiber content. In addition, the carbon fiber content showed a slight influence on the fiber orientation in the contact-hardening composites.

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Different testing methods for assessing the synthetic fiber distribution in cement-based composites

Cited by 55 publications

References 45 publications

Mechanical Properties of SiO₂‐Coated Carbon Fiber‐Reinforced Mortar Composites with Different Fiber Lengths and Fiber Volume Fractions

Mechanical Properties of SiO₂‐Coated Carbon Fiber‐Reinforced Mortar Composites with Different Fiber Lengths and Fiber Volume Fractions

Prediction of Geopolymer Concrete Compressive Strength Using Novel Machine Learning Algorithms

Quantitative Evaluation of Carbon Fiber Dispersion in Amorphous Calcium Silicate Hydrate-Based Contact-Hardening Composites

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Different testing methods for assessing the synthetic fiber distribution in cement-based composites

Cited by 55 publications

References 45 publications

Mechanical Properties of SiO2‐Coated Carbon Fiber‐Reinforced Mortar Composites with Different Fiber Lengths and Fiber Volume Fractions

Mechanical Properties of SiO2‐Coated Carbon Fiber‐Reinforced Mortar Composites with Different Fiber Lengths and Fiber Volume Fractions

Prediction of Geopolymer Concrete Compressive Strength Using Novel Machine Learning Algorithms

Quantitative Evaluation of Carbon Fiber Dispersion in Amorphous Calcium Silicate Hydrate-Based Contact-Hardening Composites

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Mechanical Properties of SiO₂‐Coated Carbon Fiber‐Reinforced Mortar Composites with Different Fiber Lengths and Fiber Volume Fractions

Mechanical Properties of SiO₂‐Coated Carbon Fiber‐Reinforced Mortar Composites with Different Fiber Lengths and Fiber Volume Fractions