Compressive strength modelling of cenosphere and copper slag-based geopolymer concrete using deep learning model.

Journal: Scientific reports
Published Date: Jul 30, 2025

Abstract

Geopolymer concrete (GPC) is an eco-friendly alternative for conventional concrete. It exploits industrial by-products in production to reduce the environmental impact and improve sustainability. This study focuses on envisaging the 28-day compressive strength of cenosphere-based geopolymer concrete incorporating copper slag using Artificial Neural Networks (ANN). The assimilation of ANN models in predicting the compressive strength of cenosphere-based geopolymer concrete with copper slag offers a promising approach to sustainable construction. By precisely forecasting the compressive strength of concrete based on the ingredient proportions, these models can rationalise the design process. The test results signposted that the developed model gives higher accuracy (> 98.6%), capability and flexibility in predicting the compressive strength of geo-polymer concrete incorporated with cenosphere and copper slag.

Authors

  • G K Arunvivek
    Department of Civil Engineering, Mohan Babu University, Tirupati, 517102, Andhra Pradesh, India.
  • S Anandaraj
    Department of Civil Engineering, KPR Institute of Engineering and Technology, Coimbatore, India.
  • Pramod Kumar
    Centre for Interdisciplinary and Mathematical Sciences, BHU, India.
  • Bheem Pratap
    Department of Civil Engineering, Graphic Era Deemed to be University, Dehradun, India.
  • Regasa Yadeta Sembeta
    Department of Civil Engineering, College of Engineering and Technology, Mattu University, Metu, Ethiopia. regasa.yadeta@meu.edu.et.

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