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Seasonal Performance Evaluation of Pavement Base Using Recycled Materials

Author

Listed:
  • Yang Zhang

    (School of Transportation, Southeast University, Nanjing 211189, China)

  • Bora Cetin

    (Department of Civil and Environmental Engineering, Michigan State University, East Lansing, MI 48824, USA)

  • Tuncer B. Edil

    (Civil and Environmental Engineering Department, University of Wisconsin-Madison, Madison, WI 53706, USA)

Abstract

Using recycled pavement materials to construct new pavement base is currently an important construction strategy bringing improved sustainability. This study investigates the long-term performance of pavement bases constructed with recycled concrete aggregate (RCA), reclaimed asphalt pavement (RAP), and blends with natural aggregates in a seasonal frost region. The stabilization effect of fly ash on RAP was studied as well. In situ falling weight deflectometer (FWD) tests were routinely conducted to provide seasonal deflection data, which were used to back-calculate the layer modulus. Seasonal changes in the base layer modulus along with the pavement ride quality were monitored. One of the two lanes at the test sections was consistently subjected to traffic loading, whereas the other one was not. Findings from this field research indicated that after undergoing over 8 years of naturally seasonal freeze-thaw conditions, 100% RCA, 50% RCA, plus 50% natural aggregates, and 100% RAP, presented improved performance over 100% natural aggregates. However, 50% RAP blended with 50% natural aggregates performed comparably to natural aggregates only, and fly ash did not provide considerable improvement on the long-term performance of 50% RAP plus 50% natural aggregate base. Seasonal climatic variations turned out to affect pavement performance more critically than traffic loading.

Suggested Citation

  • Yang Zhang & Bora Cetin & Tuncer B. Edil, 2021. "Seasonal Performance Evaluation of Pavement Base Using Recycled Materials," Sustainability, MDPI, vol. 13(22), pages 1-15, November.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:22:p:12714-:d:681086
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    References listed on IDEAS

    as
    1. Volker Liermann & Sangmeng Li, 2021. "Methods of Machine Learning," Springer Books, in: Volker Liermann & Claus Stegmann (ed.), The Digital Journey of Banking and Insurance, Volume III, pages 225-238, Springer.
    2. Cetin, Bora & Aydilek, Ahmet H. & Guney, Yucel, 2010. "Stabilization of recycled base materials with high carbon fly ash," Resources, Conservation & Recycling, Elsevier, vol. 54(11), pages 878-892.
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