Publicacións

@article{rojo-lopez_genetic_2024,

title = {Genetic programming to understand the influence of new sustainable powder materials in the fresh performance of cement pastes},

author = {Gemma Rojo-López and Belén González-Fonteboa and Juan Luis Pérez-Ordóñez and Fernando Martínez-Abella},

url = {https://www.sciencedirect.com/science/article/pii/S235271022400754X},

doi = {10.1016/j.jobe.2024.109186},

issn = {2352-7102},

year  = {2024},

date = {2024-07-01},

urldate = {2024-07-01},

journal = {Journal of Building Engineering},

volume = {88},

pages = {109186},

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 = {Artificial intelligence, Biomass ash, Granite powder, Metakaolin, Parametric analysis},

pubstate = {published},

tppubtype = {article}

}

@article{Rojo-López2024,

title = {Genetic programming to understand the influence of new sustainable powder materials in the fresh performance of cement pastes},

author = {Gemma Rojo-López and Belén González-Fonteboa and Juan Luis Pérez-Ordóñez and Fernando Martínez-Abella},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189693470&doi=10.1016%2fj.jobe.2024.109186&partnerID=40&md5=82b0d972a8049ef5dccd64581bae8dd4},

doi = {10.1016/j.jobe.2024.109186},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

journal = {Journal of Building Engineering},

volume = {88},

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. © 2024 The Author(s)},

note = {Cited by: 0; All Open Access, Green Open Access, Hybrid Gold Open Access},

keywords = {Biomass ashes, Cement paste, Cements, Fresh performance, Genetic algorithms, Genetic programming, Granite, Granite powder, Metakaolins, Parametric analysis, Performance of cement, Powder material, Rheological property, Rheology, Supplementary cementitious material, Yield stress},

pubstate = {published},

tppubtype = {article}

}

@article{rojo-lopez_parametric_2023,

title = {Parametric analysis in sustainable self-compacting mortars using genetic programming},

author = {Gemma Rojo-López and Belén González-Fonteboa and Juan Luis Pérez-Ordóñez and Fernando Martínez-Abella},

url = {https://www.sciencedirect.com/science/article/pii/S0950061823029069},

doi = {10.1016/j.conbuildmat.2023.133189},

issn = {0950-0618},

year  = {2023},

date = {2023-11-01},

urldate = {2023-11-01},

journal = {Construction and Building Materials},

volume = {404},

pages = {133189},

abstract = {This study addresses the capabilities of genetic programming to predict the behaviour of cement-based mixtures by focusing on the influence of quaternary binders (incorporating metakaolin, biomass ash and granite powder as novel powder materials) on the rheological properties of self-compacting mixtures, including spread diameter in mini-cone test and time to flow in mini-funnel test. Using a previous dataset, GP techniques are applied to obtain predicted models and to compare them with those developed throughout analysis of variance. The results demonstrate that the equations obtained by the GP technique showed the best statistical indices for the analysed properties. Afterwards, a parametric analysis was performed to analyse the influence of the composition of quaternary binders on the fresh behaviour of mortar mixtures. The parametric analysis indicated that changes in the binder composition that increased granite powder content damage the fresh behaviour of the mortars (the funnel time increases, and the spread diameter decreases), being this negative effect more significant when the water content is low, and especially noteworthy in the Tfunnel time. It is concluded that genetic programming and design of experiments are powerful tools that can be used to analyse the influence of new raw materials in different mortar properties.},

keywords = {Biomass ash, Genetic programming, Granite powder, Supplementary cementitious materials},

pubstate = {published},

tppubtype = {article}

}