Genetic programming to understand the influence of new sustainable powder materials in the fresh performance of cement pastes
Created by W.Langdon from
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- @Article{ROJOLOPEZ:2024:jobe,
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author = "Gemma Rojo-Lopez and Belen Gonzalez-Fonteboa and
Juan Luis Perez-Ordonez and Fernando Martinez-Abella",
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title = "Genetic programming to understand the influence of new
sustainable powder materials in the fresh performance
of cement pastes",
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journal = "Journal of Building Engineering",
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volume = "88",
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pages = "109186",
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year = "2024",
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ISSN = "2352-7102",
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DOI = "doi:10.1016/j.jobe.2024.109186",
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URL = "https://www.sciencedirect.com/science/article/pii/S235271022400754X",
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keywords = "genetic algorithms, genetic programming, Biomass ash,
Granite powder, Metakaolin, Artificial intelligence,
Parametric analysis, XAI",
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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",
- }
Genetic Programming entries for
Gemma Rojo-Lopez
Belen Gonzalez-Fonteboa
Juan Luis Perez
Fernando Martinez Abella
Citations