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<p>Using powdered glass in construction materials has emerged as a sustainable and innovative strategy to improve the properties of concrete, mortar and other construction composites. The present research uses waste glass powder from liquid crystal displays in green refractory mortar to manage electronic glass waste. The study examines the effectiveness of artificial neural networks and response surface methodology models in predicting the mechanical characteristics and ultrasonic pulse velocity of the developed mortar. The research includes modelling with different percentages of e-waste glass replacing dune sand at temperatures ranging from 200 to 800&#xa0;°C over two hours. The results show that e-glass waste powder variable influenced the characteristics strength of dune sand mortar at higher temperature, days (<i>P</i> &lt; 0.05). The model predicted values in both techniques were in close agreement with corresponding experimental values in all cases. However, the results show that the artificial neural network consistently provides values comparable or superior to the response surface methodology models, demonstrating its potential feasibility through statistical measures such as coefficient of determination (R<sup>2</sup>), root mean square error, and mean absolute deviation and the variations of the residuals prediction indicate the functionality of both modeling approaches for E-glass waste mortar strength prediction. This empirical method is useful for determining the thermo-physical and thermo-mechanical properties of e-waste glassy refractory mortar. The incorporation of powdered E-glass waste into construction materials presents a promising opportunity to enhance sustainability, structural integrity, and aesthetic appeal. Utilizing powder glass as an insulating material in construction holds significant potential to improve thermal performance while promoting sustainability and mitigating the risk of explosive spalling. Its applications across various building elements can enhance energy efficiency and benefits for both the environment and the built environment.</p>

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Predicting the sustainability of e-waste mortar for mitigating thermal spalling cracks using ANN and RSM

  • 期刊论文

  • 发表日期：

    2025年3月27日

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  • Y. Abadou,
  • A. Ghrieb,
  • T. Choungara,
  • H. Faid

摘要

Using powdered glass in construction materials has emerged as a sustainable and innovative strategy to improve the properties of concrete, mortar and other construction composites. The present research uses waste glass powder from liquid crystal displays in green refractory mortar to manage electronic glass waste. The study examines the effectiveness of artificial neural networks and response surface methodology models in predicting the mechanical characteristics and ultrasonic pulse velocity of the developed mortar. The research includes modelling with different percentages of e-waste glass replacing dune sand at temperatures ranging from 200 to 800 °C over two hours. The results show that e-glass waste powder variable influenced the characteristics strength of dune sand mortar at higher temperature, days (P < 0.05). The model predicted values in both techniques were in close agreement with corresponding experimental values in all cases. However, the results show that the artificial neural network consistently provides values comparable or superior to the response surface methodology models, demonstrating its potential feasibility through statistical measures such as coefficient of determination (R2), root mean square error, and mean absolute deviation and the variations of the residuals prediction indicate the functionality of both modeling approaches for E-glass waste mortar strength prediction. This empirical method is useful for determining the thermo-physical and thermo-mechanical properties of e-waste glassy refractory mortar. The incorporation of powdered E-glass waste into construction materials presents a promising opportunity to enhance sustainability, structural integrity, and aesthetic appeal. Utilizing powder glass as an insulating material in construction holds significant potential to improve thermal performance while promoting sustainability and mitigating the risk of explosive spalling. Its applications across various building elements can enhance energy efficiency and benefits for both the environment and the built environment.