Fracture properties and response surface methodology model of alkali-slag concrete under freeze–thaw cycles

Li, Qixuan; Cai, Liangcai; Fu, Yucan; Wang, Haifu; Zou, Yong Cun

doi:10.1016/j.conbuildmat.2015.06.037

Cited by 59 publications

(11 citation statements)

References 21 publications

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“…The response surface methodology (RSM) [41] consists of a collection of statistical-mathematical techniques applied to the creation of data adjustment models by means of which a series of parameters may be optimized and find the interactions that are produced between them [43,44]. It is a common method used in the improvement, development, and process management [45] in various industries, which has also been applied to those of concrete and cement for the design of mixtures [46][47][48][49][50][51], the analysis of resistant behavior [52][53][54][55][56], or the influence that the fiber content and the aspect ratio have in the optimization of the fracture of the fiber reinforced concrete [57].…”

Section: Response Surface Methodologymentioning

confidence: 99%

Study of the Compression Behavior of Steel-Fiber Reinforced Concrete by Means of the Response Surface Methodology

2019

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The compression behavior of steel-fiber reinforced concrete (SFRC) has been addressed exhaustively in recent decades thereby highlighting a variety of differences with regard to the effect that the addition of fiber has on it. In this paper, a detailed study of the subject is developed for which a database has been created, which includes 197 tests performed on cylindrical concrete specimens with dimensions of 150 × 300 mm 2 (diameter × height). By means of the response surface methodology, we disclose the relationship that exists between the geometric parameters of the fiber (length, diameter, and aspect ratio), their amount (fraction in volume), and some matrix parameters (compression resistance and maximum size of coarse aggregate) with the different compression responses of the SFRC, which are strength, elastic modulus, critical deformation under maximum load, and the volumetric deformation work in the pre- and post-peak branch. Linear polynomial models are chosen to adjust each response with the defined factors, and said variables are studied in a dimensional and non-dimensional format. From the results obtained, it is verified how the inclusion of steel-fibers produces notable improvements in ductility and the energy absorption capacity of the concrete when significantly increasing the works of volumetric deformation in the pre- and post-peak branch with respect to the matrix without fibers. In addition, a new model is analyzed, which describes the stress–strain curve of the compression behavior of the SFRC based on the increase of ductility and energy absorption. This model is characterized by a softening branch subsequent to the peak load determined by means of the residual compressive strength, a parameter that corresponds to the value of the compressive stress associated with a strain equal to three times that of the peak of the curve, which is significantly dependent on the aspect ratio and fiber content.

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Section: Response Surface Methodologymentioning

confidence: 99%

Study of the Compression Behavior of Steel-Fiber Reinforced Concrete by Means of the Response Surface Methodology

2019

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“…In Fig. 4b elliptical contour lines were obtained meaning there is a perfect interaction between variables [10] and [24], the elliptical shape contours also show that there is an area of optimum performance within 1.5 -2.5% nanosilica and 4 -5.5% binder content. 5 depicts the effects of variation in both nanosilica and binder content on the asphalt mixtures.…”

Section: Volumetric Responses Analysismentioning

confidence: 99%

Application of Response Surface Methodology for Mix Design Optimization of Nanocomposite Modified Asphalt Mixtures

Bala¹

2017

GEOMATE

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ABSTRACT:Recently the application of polymer nanocomposite has been increasingly recognized as an alternative to polymer modified binders for durable asphalt mixtures. In this study, the optimization of nanosilica and binder content for nanocomposite modified asphalt mixtures has been examined to obtain optimum quantities for higher volumetric properties. Response Surface Methodology (RSM) based on face centered central composite design (FCCCD) was utilized. Interaction effects of independent variables nanosilica and binder content on nanocomposite volumetric properties namely stability, flow, void in total mix (VTM) and voids in mineral aggregate (VMA) were evaluated. The result indicates that the individual effects of nanosilica and binder content are both important; however, the asphalt binder content had more significance on the volumetric properties. Higher Stability was achieved with the mixtures prepared with 2% nanosilica and binder content range of 5 -6%. Also, the mean error obtained in all the responses from optimization results are all less than 5%, this indicates that predicted values are in agreement with experimental results. Furthermore, it was concluded that asphalt mixture design with high performance properties, optimization using RSM is a very effective approach.

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“…Ghesal and Khayat [14] utilized factorial design and RSM to optimize a four-component concrete containing limestone filler subject to eight performance criteria. Li et al [15] utilized Boh-Behnken experiments and response surface method to model alkali slag concrete of normal concrete under freeze-thaw cycles. Islam et al [9] conducted statistical method to predict the strength of HPC incorporating RHA for compressive strength in the varying of 40-90 MPa.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Mixture Proportions of High Strength High Performance Concrete Incorporating Rice Husk Ash by Using Response Surface Methodology

Bahri¹,

Mahmud²,

Shafigh³

2019

Proceedings of the Proceedings of the 1st Workshop on Multidisciplinary and Its Applications Part 1, WMA-01 2018, 19-20 January

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Five key variables of high-strength high performance concrete (HSHPC) were considered in the models developed such as water-to-binder ratios (w/b), binder contents, percentages of partial cement replacement with rice husk ash (RHA), ratios of fine aggregate to total aggregate (fa/ta), and percentages of superplasticizer dosage. Box Behnken Design (BBD) experiment and response surface methodology (RSM) were applied to determine the models that can optimize mix proportion consisting of the five variables with three levels leading to optimal slump value, compressive strength at age of 1 and 28-days. The quadratic model is statistically acceptable compared other models. The prediction of optimum values and the clarification of the interactions between the specified range factors were done by using the quadratic model and analysis of variance (ANOVA). The models were able to accurately predict the response of slump and compressive strength of HSHPC less than 5% error. The results proved that the models show that ratio w/b, binder contents, percentages of partial cement replacement with RHA and percentages of superplasticizer dosage have a significant effect on the slump and compressive strength of concrete. It shows that the proposed response models provide useful information regarding the mixture optimization for securing target strength and cost-effective of HSHPC.

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Fracture properties and response surface methodology model of alkali-slag concrete under freeze–thaw cycles

Cited by 59 publications

References 21 publications

Study of the Compression Behavior of Steel-Fiber Reinforced Concrete by Means of the Response Surface Methodology

Study of the Compression Behavior of Steel-Fiber Reinforced Concrete by Means of the Response Surface Methodology

Application of Response Surface Methodology for Mix Design Optimization of Nanocomposite Modified Asphalt Mixtures

Optimization of Mixture Proportions of High Strength High Performance Concrete Incorporating Rice Husk Ash by Using Response Surface Methodology

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