Optimization of Green Concrete Containing Fly Ash and Rice Husk Ash Based on Hydro-Mechanical Properties and Life Cycle Assessment Considerations

Fly Ash Rice Husk Ash Concrete Hydro-Mechanical Properties Sustainable Concrete Concrete Life Cycle Assessment.

Authors

  • Kennedy C. Onyelowe Department of Civil Engineering, Michael Okpara University of Agriculture Umudike, 440109, Umuahia,, Uganda
  • Ahmed M. Ebid
    ahmed.abdelkhaleq@fue.edu.eg
    Faculty of Engineering and Technology, Future University in Egypt, New Cairo 11865,, Egypt http://orcid.org/0000-0002-3392-4424
  • Hisham A. Mahdi Faculty of Engineering and Technology, Future University in Egypt, New Cairo 11865,, Egypt
  • Atefeh Soleymani Department of Civil Engineering, Shahid Bahonar University of Kerman, Kerman,, Iran, Islamic Republic of
  • Hashem Jahangir Department of Civil Engineering, University of Birjand, Birjand,, Iran, Islamic Republic of
  • Farshad Dabbaghi Department of Civil Engineering, Babol Norshivani University of Technology, Mazandaran,, Iran, Islamic Republic of

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The development of sustainable concrete in achieving the developmental goals of the United Nations in terms of sustainable infrastructure and innovative technology forms part of the focus of this research paper. In order to move towards sustainability, the utilization of the by-products of agro-industrial operations, which are fly ash (FA) and rice husk ash (RHA), in the production of concrete has been studied. Considering the environmental impact of concrete constituents, multiple mechanical and hydraulic properties of fly ash (FA) and rice husk ash (RHA) concrete have been proposed using intelligent techniques; artificial neural network (ANN) and evolutionary polynomial regressions (EPR). Also, an intelligent mix design tool/chart for this case under study is proposed. Multiple data points of concrete materials, which were further reduced to ratios as follows; cement to binder ratio (C/B), aggregate to binder ratio (Ag/B), and plasticizer to binder ratio (PL/B) were used in this exercise. At the end of the protocol, it is observed that the constituents' ratios are dependent on the behavior of the whole, which can be solved by using the proposed model equations and mix design charts. The models performed optimally, as none showed any performance below 80%. However, ANN, which predicted Fc03, Fc07, Fc28, Fc60, Fc90, Ft28, Ff28 & Fb28, S, Ec28 & K28, and P with an accuracy of greater than 95% each with average error of less than 9.4% each, is considered the decisive technique in predicting all the studied concrete properties, including the life cycle assessment potential of the concrete materials.

 

Doi: 10.28991/CEJ-2022-08-12-018

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