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Performance Evaluation of Asphalt Mixtures Containing Different Proportions of Alternative Materials

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  • المصدر:
    Sustainability
  • نوع التسجيلة:
    Electronic Resource
  • الدخول الالكتروني :
    http://grafar.grf.bg.ac.rs/bitstream/id/11962/sustainability-15-13314.pdf
    The Fulbright Visiting Scholar Program, sponsored by the U.S. Department of State
    info:eu-repo/grantAgreement/MESTD/inst-2020/200092/RS
  • معلومة اضافية
    • Publisher Information:
      MDPI 2023
    • Added Details:
      Khorshidi, Meisam
      Goli, Ahmad
      Orešković, Marko
      Khayambashi, Kamiar
      Ameri, Mahmoud
    • نبذة مختصرة :
      With the increasing scarcity and cost of virgin materials for asphalt mixtures, the exploration of alternative components has intensified. Reclaimed asphalt pavement (RAP), crumb rubber (CR), steel slag (SS), and waste engine oil (WEO) have emerged as promising alternatives. Individually, RAP enhances rutting resistance but may compromise cracking tolerance; CR boosts cracking resistance; WEO affects cracking and rutting differently; and SS can influence moisture sensitivity. However, their combined impacts on asphalt performance, specifically on moisture damage, rutting, and cracking resistance, remain underexplored. In this study, 44 mixtures were assessed with varying RAP (0–75%), WEO (0–15%), and CR (0–15%) contents, alongside a constant SS aggregate (0% or 20%). The results indicate that specific combinations of these alternative materials can satisfy all performance thresholds for rutting, cracking, and moisture damage. To pinpoint ranges of optimal material contents for different high-traffic scenarios, prediction models were crafted using techniques like feed-forward neural network (FNN), generalized linear model (GLM), support vector regression (SVM), and Gaussian process regression (GPR). Among these, GPR demonstrated superior efficacy, effectively identifying regions of satisfactory performance.
    • الموضوع:
    • Note:
      Sustainability
      English
    • Other Numbers:
      RSPST oai:grafar.grf.bg.ac.rs:123456789/3172
      2071-1050
      https://grafar.grf.bg.ac.rs/handle/123456789/3172
      10.3390/su151813314
      1405302936
    • Contributing Source:
      UIVERSITY OF BELGRADE
      From OAIster®, provided by the OCLC Cooperative.
    • الرقم المعرف:
      edsoai.on1405302936
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