Journal of Structural and Construction Engineering

Journal of Structural and Construction Engineering

Presenting an Optimized Artificial Intelligent Models to Investigate the Strength Behavior of Sustainable Concrete Containing Recycled Polyethylene Terephthalate-based Fine Aggregate

Document Type : Original Article

Authors
Mahdi Mirzagoltabar Roshan 1
Mohammadhadi AlizadeElizei 2
Reza Esmaeilabadi 3
1 PhD candidate, Department of civil engineering, Roudehen Branch, Islamic Azad University, Roudehen, Iran
2 Department of civil engineering, Roudehen Branch, Islamic Azad University, Roudehen, Iran
3 Assistant professor , Department of Civil Engineering, Roudehen Branch,Tehran, Iran,
10.22065/jsce.2021.282089.2430
Abstract
In this research, optimized intelligent models were developed to design optimal sustainable concrete containing recycled Polyethylene Terephthalate (PET). For this aim, evolutionary Artificial Intelligence (AI) approach was implemented based on the integration of the Multivariate Adaptive Regression Splines (MARS) and Extreme Learning Machine (ELM) integrated with particle swarm optimization algorithm to investigate the strength behavior of sustainable concrete containing recycled polyethylene terephthalate-based fine aggregate. The experimental database consisting 273 records comprising mixture components at different ages are collected from published papers and optimal variables are identified using principal component analysis. The capability and efficiency of proposed model are validated through standalone MARS and ELM. Performance metrics indicated that proposed evolutionary formula-based models (MARS-PSO and ELM-PSO with the ((R= 0.902, RMSE=4.836 MPa and RSE=3.5) and (R= 0.900, RMSE=4.881 MPa and RSE=2.24), respectively) outperformed than other standalone AI models for CS prediction. Uncertainty analysis of the standalone and hybridized models is also applied using Monte-carlo simulation to prove that the hybridized multiscale model has less uncertainty in the prediction of the compressive strength compared to those benchmark models. The findings of the present paper presented the superiority of the model’s development in constructing reasonable and robustness evolutionary Model for formulation of CS of eco-friendly concrete containing recycled PET.
Keywords
Sustainable concrete Polyethylene terephthalate (PET)
Artificial intelligence
MARS
Extreme learning machine
Monte-Carlo simulation

Subjects

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  • Receive Date 19 April 2021
  • Revise Date 10 August 2021
  • Accept Date 24 October 2021