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Computers and Concrete
  Volume 26, Number 2, August 2020, pages 175-183
DOI: http://dx.doi.org/10.12989/cac.2020.26.2.175
 


A model to characterize the effect of particle size of fly ash on the mechanical properties of concrete by the grey multiple linear regression
Yunpeng Cui, Jun Liu, Licheng Wang, Runqing Liu and Bo Pang

 
Abstract
    Fly ash has become an important component of concrete as supplementary cementitious material with the development of concrete technology. To make use of fly ash efficiently, four types of fly ash with particle size distributions that are in conformity with four functions, namely, S.Tsivilis, Andersen, Normal and F distribution, respectively, were prepared. The four particle size distributions as functions of the strength and pore structure of concrete were thereafter constructed and investigated. The results showed that the compressive and flexural strength of concrete with the fly ash that conforming to S.Tsivilis, Normal, F distribution increased by 5-10 MPa and 1-2 MPa, respectively, compared to the reference sample at 28 d. The pore structure of the concrete was improved, in which the total porosity of concrete decreased by 2-5% at 28 d. With regarding to the fly ash with Andersen distribution, it was however not conducive to the strength development of concrete. Regression model based on the grey multiple linear regression theory was proved to be efficient to predict the strength of concrete, according to the characteristic parameters of particle size and pore structure of the fly ash.
 
Key Words
    fly ash; particle size; concrete; grey multiple linear regression
 
Address
Yunpeng Cui: Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian, China
Jun Liu: School of Materials Science and Engineering, Shenyang Ligong University, Shenyang, China
Licheng Wang: Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian, China
Runqing Liu: School of Materials Science and Engineering, Shenyang Ligong University, Shenyang, China
Bo Pang: Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian, China
 

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