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ISSN 2753-3239
CCC: 3
PROCEEDINGS OF THE FOURTEENTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL STRUCTURES TECHNOLOGY
Edited by: B.H.V. Topping and J. Kruis
Paper 21.1

Designing eco-friendly cement composites mixtures aided by artificial neural networks

S. Czarnecki and M. Moj

Department of Building Engineering, Wroclaw University of Science and Technology, Wroclaw, Poland

Full Bibliographic Reference for this paper
S. Czarnecki, M. Moj, "Designing eco-friendly cement composites mixtures aided by artificial neural networks", in B.H.V. Topping, J. Kruis, (Editors), "Proceedings of the Fourteenth International Conference on Computational Structures Technology", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 3, Paper 21.1, 2022, doi:10.4203/ccc.3.21.1
Keywords: eco-friendly cement composites, artificial neural networks, granite powder, fly ash, modelling structures.

Abstract
The paper predicts the pull-off strength of the substrate layer of a cementitious composite containing granite powder and fly ash replacing up to 30% of the cement weight. For this purpose, intelligent artificial neural network (ANN) models were used and compared. A database was built based on and mix composition, curing time and curing method, and non-destructive Schmidt hammer compressive strength measurements. The model developed to predict the pull-off strength of the substrate layer of cementitious composites containing granite powder and fly ash was shown to be accurate. This method can be used especially for designing cement mortars with granite powder and fly ash additives replacing cement in the range of 0% to 30% of its weight. These mortars can be used for floor substrates.

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