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Transportation infrastructure greatly impacts society's everyday existence. Highway authorities prioritize cost-effective design methods. Engineers are studying Rock Wool Fiber for the market as a pavement improvement. Resource Waste Reduction Framework (RWF) helps save natural resources and use waste. Asphalt concrete needs strong tensile strength to resist cracking and structural failure from traffic loads, temperature variations, and environmental conditions. Rock wool may improve asphalt concrete tensile strength. This research examines how rock wool affects asphalt concrete tensile properties. Tests were performed to determine tensile strength under normal and defined settings, and the impact of unconditional and conditional testing on TSR. Tensile strength is maximum with 0.80% rock wool and unconditional samples are stronger than conditional ones. Models and mixed proportions were designed using RSM. Each reaction is predicted by an equation, and experimental validation is done using optimized responses.

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Enhancing Tensile Strength of Asphalt Concrete Through Rock Wool Inclusion

  • 会议论文

  • 发表日期：

    2025年

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  • Muhammad Basit Khan,
  • Nasir Shafiq,
  • Abdul Mateen khan,
  • Ahsan Waqar,
  • Nawab Sameer Zada

摘要

Transportation infrastructure greatly impacts society's everyday existence. Highway authorities prioritize cost-effective design methods. Engineers are studying Rock Wool Fiber for the market as a pavement improvement. Resource Waste Reduction Framework (RWF) helps save natural resources and use waste. Asphalt concrete needs strong tensile strength to resist cracking and structural failure from traffic loads, temperature variations, and environmental conditions. Rock wool may improve asphalt concrete tensile strength. This research examines how rock wool affects asphalt concrete tensile properties. Tests were performed to determine tensile strength under normal and defined settings, and the impact of unconditional and conditional testing on TSR. Tensile strength is maximum with 0.80% rock wool and unconditional samples are stronger than conditional ones. Models and mixed proportions were designed using RSM. Each reaction is predicted by an equation, and experimental validation is done using optimized responses.