2017
DOI: 10.1016/j.jobe.2016.12.004
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Effect of fly ash and grading agent on the properties of mortar using response surface methodology

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Cited by 35 publications
(13 citation statements)
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“…Using a p-value of 0.05, variance analysis was employed to calculate the significance level of the variables. The key and interactive terms of the variables with p-values lower than 0.05 were regarded as significant in affecting the model responses, whereas p-values greater than 0.05 were regarded insignificant [33,34]. For prediction models, only significant terms are dealt with except those needed to sustain the order of the model.…”
mentioning
confidence: 99%
“…Using a p-value of 0.05, variance analysis was employed to calculate the significance level of the variables. The key and interactive terms of the variables with p-values lower than 0.05 were regarded as significant in affecting the model responses, whereas p-values greater than 0.05 were regarded insignificant [33,34]. For prediction models, only significant terms are dealt with except those needed to sustain the order of the model.…”
mentioning
confidence: 99%
“…Although the optimum values can be found, it is difficult to identify the optimum regions intuitively. Actually, a conventional methodology of one factor at a time (OFAT), which means a single factor for a specific experimental design with other factors maintained constant, has been blamed for failing to provide expected output as the interaction effects among variables are not correctly examined [21]. On the contrary, RSA as an optimization method is created to undertake the central composite design (CCD).…”
Section: Methodsmentioning
confidence: 99%
“…Theoretically, it is a key statistical method for solving multivariate problems. RSM is widely used in research to identify the optimum solution by analyzing variables which affect final results [21,22,23,24,25,26].…”
Section: Methodsmentioning
confidence: 99%
“…Mohammed, et al [11], has utilized RSM to model the compressive strength of concrete containing paper mill as additives. Mtarfi, et al [12], have optimized and developed model for predicting mortar compressive strength with RSM. Güneyisi, et al [13] have developed models and optimized high-performance concrete by minimizing the durability factors and maximizing compressive strength using metakoalin and fly ash as variables.…”
Section: Introductionmentioning
confidence: 99%