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    Drying shrinkage of self-compacting concrete incorporating fly ash

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    Author
    Abdalhmid, Jamila M.A.
    Supervisor
    Ashour, Ashraf F.
    Sheehan, Therese
    Keyword
    Self-compacting concrete
    Drying shrinkage
    Fly ash
    Prediction
    Artifical neural networks
    Rights
    Creative Commons License
    The University of Bradford theses are licenced under a Creative Commons Licence.
    Institution
    University of Bradford
    Department
    Faculty of Engineering and Informatics
    Awarded
    2019
    
    Metadata
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    Abstract
    The present research is conducted to investigate long term (more than two years) free and confined drying shrinkage magnitude and behaviour of self-compacting concrete (SCC) and compare with normal concrete (NC). For all SCCs mixes, Portland cement was replaced with 0-60% of fly ash (FA), fine and coarse aggregates were kept constant at 890 kg/m3 and 780 kg/m3, respectively. Two different water binder ratios of 0.44 and 0.33 were examined for both SCCs and NCs. Fresh properties of SCCs such as filling ability, passing ability, viscosity and resistance to segregation and hardened properties such as compressive and flexural strengths, water absorption and density of SCCs and NCs were also determined. Experimental results of free drying shrinkage obtained from this study together with collected comprehensive database from different sources available in the literature were compared to five existing models, namely the ACI 209R-92 model, BSEN-92 model, ACI 209R-92 (Huo) model, B3 model, and GL2000 model. To assess the quality of predictive models, the influence of various parameters (compressive strength, cement content, water content and relative humidity) on the drying shrinkage strain are studied. An artificial neural network models (ANNM) for prediction of drying shrinkage strains of SCC was developed using the same data used in the existing models. Two ANNM sets namely ANNM1 and ANNM2 with different numbers of hidden layer neurones were constructed. Comparison between the results given by the ANNM1 model and the results obtained by the five existing predicted models were presented. The results showed that, using up to 60% of FA as cement replacement can produce SCC with a compressive strength as high as 30 MPa and low drying shrinkage strain. SCCs long-term drying shrinkage from 356 to 1000 days was higher than NCs. Concrete filled elliptical tubes (CFET) with self-compacting concrete containing FA up to 60% are recommended for use in construction in order to prevent confined drying strain. ACI 209R-92 model provided a better prediction of drying shrinkage compared with the other four models. However, a very high predictability with high accuracy was achieved with the ANNM1 model with a mean of 1.004. Moreover, by using ANNM models, it is easy to insert any of factors effecting drying shrinkage to the input parameters to predict drying shrinkage strain of SCC.
    URI
    http://hdl.handle.net/10454/17455
    Type
    Thesis
    Qualification name
    PhD
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