Genetic programming to understand the influence of new sustainable powder materials in the fresh performance of cement pastes
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Genetic programming to understand the influence of new sustainable powder materials in the fresh performance of cement pastesAuthor(s)
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2024Citation
Rojo-López, G., González-Fonteboa, B., Pérez-Ordóñez, J. L., & Martínez-Abella, F. (2024). Genetic programming to understand the influence of new sustainable powder materials in the fresh performance of cement pastes. Journal of Building Engineering, 88, 109186. https://doi.org/10.1016/j.jobe.2024.109186
Abstract
[Abstract:] This study focused on pastes that incorporate metakaolin, biomass ash, and granite powder as supplementary cementitious materials to obtain specific expressions to predict rheological properties in pastes and to define the most appropriate dosage parameters using genetic programming. For this purpose, a dataset was developed following a central composite design, and some fresh properties were measured: Marsh cone and rheological properties, such as yield stress and plastic viscosity. The models generated by genetic programming presented robust statistical indices for the properties studied. The influence of supplementary cementitious materials on rheological properties was also analysed through a parametric analysis. After analysing the factors affecting paste rheology, it was concluded that the most important aspects affecting fresh behaviour were water demand and particle interaction, as well as the relation between both effects.
Keywords
Biomass ash
Granite powder
Metakaolin
Artificial intelligence
Parametric analysis
Granite powder
Metakaolin
Artificial intelligence
Parametric analysis
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Atribución-NoComercial-SinDerivadas 3.0 España