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<p>This study aims to investigate the potential of waste marble dust powder (MDP) as a sustainable partial substitute for Ordinary Portland Cement (OPC) in M30 grade concrete and to evaluate the effect of incorporating glass fibre (GF) on the mechanical properties of the concrete. OPC was partially replaced with MDP at varying levels of 0%, 5%, 10%, and 15%. Additionally, GF was introduced at proportions of 0%, 0.5%, 1%, and 1.5% by binding material. The mechanical properties of the MDP-GF concrete mixes were assessed after a curing period of up to 28&#xa0;days. XRD diffraction theta values were measured to analyse the mineralogical changes induced by MDP incorporation. The Artificial Neural Network (ANN) model was developed to predict the strength properties based on the different combinations of MDP and GF. The experimental results demonstrated that replacing cement with MDP improved the mechanical properties of the concrete by up to 12%. The addition of GF further enhanced the flexural strength by 1.5%. The ANN model provided accurate predictions of the concrete’s mechanical properties, validating the experimental findings. This research highlights the innovative use of waste marble dust powder and glass fibre in concrete production. The findings offer valuable insights into sustainable construction practices and present a reliable predictive model for optimizing concrete mixes using these materials.</p>

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Performance evaluation of the strength properties of sustainable concrete utilizing waste marble dust and glass fibre employing artificial neural network and particle swarm optimization algorithm

  • 期刊论文

  • 发表日期：

    2025年1月23日

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  • Prashant Lahre,
  • Kundan Meshram,
  • Umank Mishra,
  • Ahmed Zubair Jan,
  • Ashhad Imam

摘要

This study aims to investigate the potential of waste marble dust powder (MDP) as a sustainable partial substitute for Ordinary Portland Cement (OPC) in M30 grade concrete and to evaluate the effect of incorporating glass fibre (GF) on the mechanical properties of the concrete. OPC was partially replaced with MDP at varying levels of 0%, 5%, 10%, and 15%. Additionally, GF was introduced at proportions of 0%, 0.5%, 1%, and 1.5% by binding material. The mechanical properties of the MDP-GF concrete mixes were assessed after a curing period of up to 28 days. XRD diffraction theta values were measured to analyse the mineralogical changes induced by MDP incorporation. The Artificial Neural Network (ANN) model was developed to predict the strength properties based on the different combinations of MDP and GF. The experimental results demonstrated that replacing cement with MDP improved the mechanical properties of the concrete by up to 12%. The addition of GF further enhanced the flexural strength by 1.5%. The ANN model provided accurate predictions of the concrete’s mechanical properties, validating the experimental findings. This research highlights the innovative use of waste marble dust powder and glass fibre in concrete production. The findings offer valuable insights into sustainable construction practices and present a reliable predictive model for optimizing concrete mixes using these materials.