Publicacións

@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{bastias_sustainable_2024,

title = {Sustainable Cement Paste Development Using Wheat Straw Ash and Silica Fume Replacement Model},

author = {Bryan Bastías and Marcelo González and Juan Rey-Rey and Guillermo Valerio and Pablo Guindos-Bretones},

url = {https://www.mdpi.com/2071-1050/16/24/11226},

doi = {10.3390/su162411226},

issn = {2071-1050},

year  = {2024},

date = {2024-01-01},

urldate = {2026-08-03},

journal = {Sustainability},

volume = {16},

number = {24},

pages = {11226},

publisher = {Multidisciplinary Digital Publishing Institute},

abstract = {Conventional cement production is a major source of carbon dioxide emissions, which creates a significant environmental challenge. This research addresses the problem of how to reduce the carbon footprint of cement paste production using agricultural and industrial waste by-products, namely wheat straw ash (WSA) and silica fume (SF). Currently, accurate models that can predict the mechanical properties of cement pastes incorporating these waste materials are lacking. To fill this gap, our study proposes a model based on response surface methodology and Box-Behnken design, designed to predict the strength of cement pastes with partial substitutions of WSA and SF. Through mechanical and characterization tests, the model demonstrated high accuracy in predicting the strength of the pastes, validated with three mixes, which showed maximum errors of less than 6% at different ages (7, 28, and 56 days). Response surface analysis revealed that replacing cement with 0–20% WSA and more than 5% SF can effectively reduce the carbon footprint by maximizing waste incorporation. This model allows for the calculation of optimal cement substitution levels based on the required strength, thus promoting sustainability in the construction industry through the use of local waste/resources.},

keywords = {Box-Behnken Design, Cement paste, design of experiment, low carbon, silica fume, Supplementary cementitious material, sustainable concrete, wheat straw ash},

pubstate = {published},

tppubtype = {article}

}