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<p>This study investigates the desiccation cracking behaviour of a locally available expansive clay mixed with quarry dust and polypropylene fibers as a barrier material. Quarry dust obtained from a stone-crushing plant in Gujarat is used to modify clay properties while reducing environmental waste. In this study, the quarry dust was added at 20% by weight of dry soil, while polypropylene fibers of length 12&#xa0;mm were added at varying proportions of 0.25%, 0.5% and 0.75%. The images of drying specimens were analysed to measure the crack features. Firstly, the crack features were manually measured using a Java-based software called ImageJ. Following this, an automatic image processing algorithm was developed to determine the crack features, minimise manual error, and increase accuracy. The crack width, Crack Intensity Factor (CIF) and Crack Reduction Ratio (CRR) were measured and compared to study the influence of quarry dust and fibers. The results from both manual and automatic procedures were compared, and the deviation in the measured values was calculated. The automated tool demonstrated improved accuracy and repeatability, with deviations from manual measurements within 1–4%, highlighting its novelty and potential for efficient crack characterization in barrier materials.</p>

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Automated Crack Characterization in Clay-Quarry Dust Blends Reinforced with Fibers Using Image Processing

  • 期刊论文

  • 发表日期：

    2026年1月27日

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  • Vanshika Makwana,
  • Anushree Ushara,
  • Panthi Sarang,
  • Mitarth Hetalkumar Soni,
  • Isha Talati,
  • Uma Chaduvula

摘要

This study investigates the desiccation cracking behaviour of a locally available expansive clay mixed with quarry dust and polypropylene fibers as a barrier material. Quarry dust obtained from a stone-crushing plant in Gujarat is used to modify clay properties while reducing environmental waste. In this study, the quarry dust was added at 20% by weight of dry soil, while polypropylene fibers of length 12 mm were added at varying proportions of 0.25%, 0.5% and 0.75%. The images of drying specimens were analysed to measure the crack features. Firstly, the crack features were manually measured using a Java-based software called ImageJ. Following this, an automatic image processing algorithm was developed to determine the crack features, minimise manual error, and increase accuracy. The crack width, Crack Intensity Factor (CIF) and Crack Reduction Ratio (CRR) were measured and compared to study the influence of quarry dust and fibers. The results from both manual and automatic procedures were compared, and the deviation in the measured values was calculated. The automated tool demonstrated improved accuracy and repeatability, with deviations from manual measurements within 1–4%, highlighting its novelty and potential for efficient crack characterization in barrier materials.