Prediction of Compressive Strength of Concretes Containing Silica Fume and Styrene-Butadiene Rubber (SBR) with a Mathematical Model

Shafieyzadeh, M.

doi:10.1007/s40069-013-0055-y

Cited by 23 publications

(22 citation statements)

References 14 publications

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“…This tendency resembles Shafieyzadeh's findings. Shafieyzadeh (2013) reported that the compressive strength of concrete with polymer-binder and SF increased about 6-15.5 %, but he used 5 % of polymer-binder ratio and 5 % of SF which was greater amount than our study. Such a high compressive strength development was attributed to the marked water-reducing effect and improved bonds between cement hydrates and aggregates due to the incorporation of polymer powder (Lho et al 2010).…”

Section: Pore Size Distributioncontrasting

confidence: 71%

“…Concrete contains mineral admixtures and latexes for various reasons at present-day. These materials can increase abrasion strength or durability and decrease permeability (Shafieyzadeh 2013). Various studies have been conducted on the durability and strength of concrete with mineral admixtures and polymers (Bhikshma et al 2009;Rozenbaum et al 2005;Wang et al 2005;Bhanjaa and Sengupta 2003).…”

Section: Introductionmentioning

confidence: 99%

“…The polymer-modified mortars using SF are expected to have excellent properties, such as high strengths, adhesion, water resistance and durability (Rossignolo 2009;Shafieyzadeh 2013).…”

Section: Introductionmentioning

confidence: 99%

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Effects of Silica Fume Content and Polymer-Binder Ratio on Properties of Ultrarapid-Hardening Polymer-Modified Mortars

Choi

Joo²,

Lho

2016

Int J Concr Struct Mater

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This paper deals with the effects of silica fume content and polymer-binder ratio on the properties of ultrarapidhardening polymer-modified mortar using silica fume and ethylene-vinyl acetate redispersible polymer powder instead of styrenebutadiene rubber latex to shorten the hardening time. The ultrarapid-hardening polymer-modified mortar was prepared with various silica fume contents and polymer-binder ratios, and tested flexural strength, compressive strength, water absorption, carbonation depth and chloride ion penetration depth. As results, the flexural, compressive and adhesion strengths of the ultrarapid-hardening polymer-modified mortar tended to increase as increasing polymer-binder ratio, and reached the maximums at 4 % of silica fume content. The water absorption, carbonation and chloride ion penetration resistance were improved according to silica fume content and polymer-binder ratio.

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Section: Pore Size Distributioncontrasting

confidence: 71%

Section: Introductionmentioning

confidence: 99%

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Effects of Silica Fume Content and Polymer-Binder Ratio on Properties of Ultrarapid-Hardening Polymer-Modified Mortars

Choi

Joo²,

Lho

2016

Int J Concr Struct Mater

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“…It is known that adding a polymeric compound to a cementitious material can improve the material properties such as strength, durability, and interfacial bond between the newly applied material and the existing substrate [1][2][3][4][5][6][7][8][9][10][11][12]. Therefore, incorporating polymers in patch repair cement mortars is common for better repair work of various reinforced concrete (RC) structures, including bridges, dams, high-rise buildings, pavements, and marine concrete structures [13][14][15][16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Influence of Polymer Types on the Mechanical Properties of Polymer-Modified Cement Mortars

Kim

2020

Applied Sciences

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This is an experimental study showing the effect of four types of polymers (acrylate polymer (AC), polyvinyl alcohol (PVA), styrene–butadiene rubber (SBR), and ethylene-vinyl acetate (EVA)) on the mechanical properties of polymer-modified cement mortars (PCMs). One polymer dosage was used in this study (3%), and the effect of this dosage on PCMs was compared with a control mortar mix with 0% polymer. The compressive, flexural, and pull-off bond strengths were measured and compared with previous results in works of literature. The effect of polymer addition on improving the mechanical properties of PCMs was clarified, and this effect was more obvious on the flexural strength than that on the compressive strength. The PCMs containing EVA showed the best performance, with up to 33% and 63% increases in compressive and flexural strengths after 28 days, respectively. In comparison, AC, PVA, and SBR produced smaller (16%–46% compared to control) improvements in the flexural strength after 28 days. In general, PCMs containing EVA showed the best mechanical properties.

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“…A lot of researchers have introduced a relationship between the concrete compressive strength and curing time with different logarithmic equations [23,[33][34][35]. Yeh, I.C.…”

Section: Concrete Compressive Strength Development Over Time Modelmentioning

confidence: 99%

Prediction Model of Compressive Strength Development in Concrete Containing Four Kinds of Gelled Materials with the Artificial Intelligence Method

Liu

Zheng

2019

Applied Sciences

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Green concrete has been widely used in recent years because its production compliments environmental conservation. The prediction of the compressive strength of concrete using non-destructive techniques is of interest to engineers worldwide. Such methods are easy to carry out because they require little or no sample preparation. Conventional models and artificial intelligence models are two main types of models to predict the compressive strength of concrete. Artificial intelligence models main include the artificial neural network (ANN) model, back propagation (BP) neural network model, fuzzy model etc. Since both conventional models and artificial intelligence models are flawed. This study proposes to build a concrete compressive strength development over time (CCSDOT) model by using conventional method combined with the artificial intelligence method. The CCSDOT model performed well in predicting and fitting the compressive strength development in green concrete containing cement, slag, fly ash, and limestone flour. It is concluded that the CCSDOT model is stable through the use of sensitivity analysis. To evaluate the precision of this model, the prediction results of the proposed model were compared to that of the model based on the BP neural network. The results verify that the recommended model enjoys better flexibility, capability, and accuracy in predicting the compressive strength development in concrete than the other models.

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Prediction of Compressive Strength of Concretes Containing Silica Fume and Styrene-Butadiene Rubber (SBR) with a Mathematical Model

Cited by 23 publications

References 14 publications

Effects of Silica Fume Content and Polymer-Binder Ratio on Properties of Ultrarapid-Hardening Polymer-Modified Mortars

Effects of Silica Fume Content and Polymer-Binder Ratio on Properties of Ultrarapid-Hardening Polymer-Modified Mortars

Influence of Polymer Types on the Mechanical Properties of Polymer-Modified Cement Mortars

Prediction Model of Compressive Strength Development in Concrete Containing Four Kinds of Gelled Materials with the Artificial Intelligence Method

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