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Predicting compressive strength of mortars containing recycled CRT glass using GMDH and GEP methods
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  • Published: 30 January 2026

Predicting compressive strength of mortars containing recycled CRT glass using GMDH and GEP methods

  • Vahid Ghorbani1,
  • Ali Seyedkazemi1 &
  • Saman Soleimani Kutanaei1 

Scientific Reports , Article number:  (2026) Cite this article

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Engineering
  • Materials science

Abstract

The growing volume of industrial and electronic waste has intensified the need for sustainable material management strategies. Among these waste streams, cathode-ray-tube (CRT) glass is of particular concern due to its high density and lead-bearing composition, which typically contains about 20–25 wt.% lead oxide. Using recycled CRT glass (RCRT) as a fine aggregate in cementitious mixtures offers a practical means of reducing landfill disposal while enhancing mortar performance. However, the mechanical behavior of RCRT-containing mortars has not been sufficiently modeled, thereby constraining the optimized design of such sustainable mixtures. In this study, two white-box, soft-computing techniques, the Group Method of Data Handling (GMDH) and Gene Expression Programming (GEP), were developed to predict the compressive strength of mortars incorporating RCRT. The database consisted of 139 laboratory specimens, and the machine-learning models were trained using the following input variables: water-to-binder ratio (w/b), water content, cement content (CC), fly ash, sand content, RCRT content, and curing time (CT). The GMDH model demonstrated superior predictive performance, achieving an R2 of 0.942 with RMSE and MAE values of 2.97 and 2.59, respectively. In contrast, the GEP model produced higher error levels (RMSE = 6.94 and MAE = 5.28). These findings indicate that transparent, data-driven modeling can capture the nonlinear interactions governing strength development in RCRT-modified mortars and provides a reliable basis for designing sustainable, dense, and mechanically efficient mixtures suitable for both conventional and radiation-shielding applications.

Data availability

The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

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The authors received no funding for this work.

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Authors and Affiliations

  1. Department of Civil Engineering, Am.C., Islamic Azad University, Amol, Iran

    Vahid Ghorbani, Ali Seyedkazemi & Saman Soleimani Kutanaei

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  1. Vahid Ghorbani
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  2. Ali Seyedkazemi
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  3. Saman Soleimani Kutanaei
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Vahid Ghorbani, Ali Seyedkazemi (corresponding author) and Saman Soleimani Kutanaei contributed to the preparation of all parts of the article.

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Correspondence to Ali Seyedkazemi.

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Ghorbani, V., Seyedkazemi, A. & Kutanaei, S.S. Predicting compressive strength of mortars containing recycled CRT glass using GMDH and GEP methods. Sci Rep (2026). https://doi.org/10.1038/s41598-026-36553-8

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  • Received: 08 October 2025

  • Accepted: 13 January 2026

  • Published: 30 January 2026

  • DOI: https://doi.org/10.1038/s41598-026-36553-8

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Keywords

  • Recycled cathode ray tube
  • Cement mortar
  • Compressive strength
  • Soft computing
  • Group method of data handling
  • Gene expression programming
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