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ORIGINAL RESEARCH article

Front. Built Environ.
Sec. Sustainable Design and Construction
Volume 10 - 2024 | doi: 10.3389/fbuil.2024.1433069

The quintenary influence of industrial wastes on the compressive strength of highstrength geopolymer concrete under different curing regimes for sustainable structures; a GSVR-XGBoost hybrid model

Provisionally accepted
Cesar Garcia Cesar Garcia 1Alexis I. Andrade Valle Alexis I. Andrade Valle 1Sabih Hashim Sabih Hashim 2Kennedy C. Onyelowe Kennedy C. Onyelowe 3*Hamza Imran Hamza Imran 4Sadiq N. Henedy Sadiq N. Henedy 5Bala M. Chilakala Bala M. Chilakala 6Manvendra Verma Manvendra Verma 7
  • 1 National University of Chimborazo, Riobamba, Chimborazo, Ecuador
  • 2 Cihan University-Erbil, Erbil, Iraq
  • 3 Michael Okpara University of Agriculture, Umudike, Nigeria
  • 4 Al-Karkh University of Science, Baghdad, Baghdad, Iraq
  • 5 Mazaya University College, Dhi-Qar, Iraq
  • 6 Vishnu Institute of Technology (VITB), Bhimavaram, Andhra Pradesh, India
  • 7 GLA University, Mathura, Uttar Pradesh, India

The final, formatted version of the article will be published soon.

    The production of geopolymer concrete (GPC) with the addition of industrial wastes as the formulation base is of interest to sustainable built environment. However, repeated experimental trials costs a huge budget, hence the prediction and validation of the strength behavior of the GPC mixed with some selected industrial wastes.Data gathering and analysis of a total 249 globally representative datasets of a high-strength geopolymer concrete (HSGPC) collected from experimental mix entries has been used in this research work. These mixes comprised of industrial wastes; fly ash (FA) and metallurgical slag (MS) and mix entry parameters like rest period (RP), curing temperature (CT), alkali ratio (AR), which stands for NaOH/Na2SiO3 ratio, superplasticizer (SP), extra water added (EWA), which was needed to complete hydration reaction, alkali molarity (M), alkali activator/binder ratio (A/B), coarse aggregate (CAgg), and fine aggregate (FAgg). These parameters were deployed as the inputs to the modeling of the compressive strength (CS). The range of CS considered in this global database was between 18 MPa and 89.6 MPa. The FA was applied between 254.54 kg/m 3 and 515 kg/m 3 while the MS was applied between 0% and 100% by weight of the FA to produce the tested HSGPC mixes. The Gaussian support vector regression hybridized with the extreme gradient boosting algorithms (GSVR-XGB) has been deployed to execute a prediction model for the studied concrete CS. The basic linear fittings to determine agreement between the parameters and the Pearson correlation between the studied parameters of the geopolymer concrete were presented. It can be observed that the CS showed very poor correlations with the values of the input parameters and required an improvement of the internal consistency of the dataset to achieve a good model performance.

    Keywords: Gaussian Support Vector Regression (GSVR), Xtreme Gradient Boosting (XGB), GSVR-XGB, High-Strength Geopolymer Concrete (HSGPC), Industrial Wastes (IW), Sustainable Concrete Structures (SCS)

    Received: 15 May 2024; Accepted: 09 Sep 2024.

    Copyright: © 2024 Garcia, Andrade Valle, Hashim, Onyelowe, Imran, Henedy, Chilakala and Verma. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Kennedy C. Onyelowe, Michael Okpara University of Agriculture, Umudike, Nigeria

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