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<p>This study explores the mechanical, durability, microstructural, and economic performance of concrete incorporating Rice Husk Biochar (RHB) and Tire Char (TC) as sustainable partial replacements for cement and fine aggregates, respectively. Sixteen concrete mixes were prepared using 0–15% RHB (by cement mass) and 0–40% TC (by sand volume). The best-performing mix (RHB0–TC40) achieved a compressive strength of 49.15&#xa0;MPa, water absorption of 2.13%, porosity of 4.26%, and durability retention of 89.68%, closely matching the control concrete. In contrast, the RHB15–TC40 mix showed reduced performance with 34.74&#xa0;MPa compressive strength and 74.16% durability retention. Microstructural analysis confirmed denser morphology in the best mix and degradation features in the poorest. ANOVA showed that RHB content had a statistically significant impact on performance metrics. Machine learning models, particularly linear regression (R² = 0.97), effectively captured strength trends. The study demonstrates that waste-derived RHB and TC can be used effectively in structural concrete, reducing reliance on virgin materials, lowering costs, and promoting circular economy practices in sustainable infrastructure development.</p>

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Performance, Durability, and Economic Viability of Sustainable Concrete Incorporating Rice Husk Biochar and Tire Char: Experimental and Machine Learning Assessment

  • 期刊论文

  • 发表日期：

    2026年3月3日

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  • Sandeep Singh,
  • A. K. Dasarathy,
  • Jagdeep Singh,
  • S. Vanitha,
  • Priyadarshi Das,
  • Gaurav Thakur

摘要

This study explores the mechanical, durability, microstructural, and economic performance of concrete incorporating Rice Husk Biochar (RHB) and Tire Char (TC) as sustainable partial replacements for cement and fine aggregates, respectively. Sixteen concrete mixes were prepared using 0–15% RHB (by cement mass) and 0–40% TC (by sand volume). The best-performing mix (RHB0–TC40) achieved a compressive strength of 49.15 MPa, water absorption of 2.13%, porosity of 4.26%, and durability retention of 89.68%, closely matching the control concrete. In contrast, the RHB15–TC40 mix showed reduced performance with 34.74 MPa compressive strength and 74.16% durability retention. Microstructural analysis confirmed denser morphology in the best mix and degradation features in the poorest. ANOVA showed that RHB content had a statistically significant impact on performance metrics. Machine learning models, particularly linear regression (R² = 0.97), effectively captured strength trends. The study demonstrates that waste-derived RHB and TC can be used effectively in structural concrete, reducing reliance on virgin materials, lowering costs, and promoting circular economy practices in sustainable infrastructure development.