2014
DOI: 10.1016/j.hbrcj.2013.09.005
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Compressive strength prediction of Portland cement concrete with age using a new model

Abstract: Based on the existing experimental data for compressive strength values of different concrete mixes, a statistical analysis for the gathered data was conducted. The analysis revealed a model for predicting the compressive strength of concrete mixes at any age with the help of two constants (A) and (B) that are considered as a characteristic property for a concrete mix. The constant (A) is introduced as a rate of strength gain constant whereas, (B) is introduced as grade of strength constant.Once the values of … Show more

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Cited by 111 publications
(28 citation statements)
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“…Moreover, Elaty [22] who did an extensive research study to predict the strength of concrete mixtures, reported values for concrete strength after 28 days of curing from Lea's Chemistry of Cement and Concrete and other references [23]. The values range from 36.1-56.5 N/mm 2 .…”
Section: Compressive Strengthmentioning
confidence: 99%
“…Moreover, Elaty [22] who did an extensive research study to predict the strength of concrete mixtures, reported values for concrete strength after 28 days of curing from Lea's Chemistry of Cement and Concrete and other references [23]. The values range from 36.1-56.5 N/mm 2 .…”
Section: Compressive Strengthmentioning
confidence: 99%
“…Normet, Jakarta, Indonesia. A common procedure was used to make the CCS samples, firstly blended sand, coarse aggregate, PCE and OPC in dry condition and then added water to make slurry in a cylindrical tube such thing as conventional concrete mixture [17][18].…”
Section: Methodsmentioning
confidence: 99%
“…Predictive model for the compressive strength of concrete with different water-to-cement ratios was given by Abram [39], which is one of the significant advancements in concrete technology [40]. Characteristics and proportioning of materials and concrete, curing, and parameters of testing are major factors, which are affecting precise measurements of compressive strength.…”
Section: Predictive Modelsmentioning
confidence: 99%