Scholarlink

<p>The unsustainable use of natural resources in construction has necessitated the exploration of eco-friendly alternatives. This study focuses on the stabilization of fly ash using hydraulic binders like lime and Ground Granulated Blast Furnace Slag (GGBS) for the Dry Lean Concrete (DLC) layer in rigid pavements. Response Surface Methodology was employed as a statistical tool for optimizing the mix proportions. According to the Analysis of Variance (ANOVA) method, the optimum mix was found to be 79% Fly Ash, 3% Lime, and 18% GGBS. To validate the statistical model, laboratory tests were conducted to measure the Unconfined Compressive Strength (UCS) of actual specimens. The predicted UCS value closely aligned with the experimentally obtained strength, thereby confirming the model’s reliability and practical utility. The study not only offers a sustainable alternative for DLC layers but also demonstrates the efficacy of using statistical tools like Response Surface Methodology and ANOVA for optimizing material mixes in construction.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Advances in Sustainable Rigid Pavements: Fly Ash Stabilization and Statistical Optimization for DLC Layer Construction

  • 期刊论文

  • 发表日期：

    2025年10月9日

查看全文
  • Hrushikesh N. Kedar,
  • Satyajit Patel

摘要

The unsustainable use of natural resources in construction has necessitated the exploration of eco-friendly alternatives. This study focuses on the stabilization of fly ash using hydraulic binders like lime and Ground Granulated Blast Furnace Slag (GGBS) for the Dry Lean Concrete (DLC) layer in rigid pavements. Response Surface Methodology was employed as a statistical tool for optimizing the mix proportions. According to the Analysis of Variance (ANOVA) method, the optimum mix was found to be 79% Fly Ash, 3% Lime, and 18% GGBS. To validate the statistical model, laboratory tests were conducted to measure the Unconfined Compressive Strength (UCS) of actual specimens. The predicted UCS value closely aligned with the experimentally obtained strength, thereby confirming the model’s reliability and practical utility. The study not only offers a sustainable alternative for DLC layers but also demonstrates the efficacy of using statistical tools like Response Surface Methodology and ANOVA for optimizing material mixes in construction.