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Development of Prediction Models for Performance of Flexible Pavements in Kansas with Emphasis on the Effects of Subgrade and Unbound Layers

Author

Listed:
  • Dunja Perić

    (Department of Civil Engineering, Kansas State University, Manhattan, KS 66506, USA)

  • Gyuhyeong Goh

    (Department of Statistics, Kansas State University, Manhattan, KS 66506, USA)

  • Javad Saeidaskari

    (Department of Civil Engineering, Kansas State University, Manhattan, KS 66506, USA)

  • Arash Saeidi Rashk Olia

    (Department of Civil Engineering, Kansas State University, Manhattan, KS 66506, USA)

  • Pooyan Ayar

    (Department of Highway and Transportation Engineering, School of Civil Engineering, Iran University of Science and Technology, Narmak, Tehran 1684613114, Iran)

Abstract

This study resulted from the need for better consideration of subgrade and unbound layers on the performance of flexible pavements in Kansas. Thus, the main objective was to develop pavement performance prediction models with emphasis on the effects of subgrade and unbound layers. To this end, pavement distress data, which were collected over several years across the state of Kansas, including rutting, fatigue cracking, transverse cracking, roughness and core analysis, served as the input data into statistical models. The effects of subgrade and unbound layers were represented by the corresponding results of dynamic cone penetrometer (DCP) tests and thickness of the unbound layer. In addition, traffic volume was represented by average annual daily truck traffic (AADTT). Multiple statistical analyses identified positive correlations of dynamic cone penetration index (DPI) and rate of total rutting, and DPI and percent of good core. Negative correlation was discovered between DPI and fatigue cracking code one, and DPI and percent of poor core. AADTT was positively correlated with transverse cracking codes one and two while it had no correlation with transverse cracking code zero. Thickness of the unbound layer was negatively correlated with pavement roughness and percent of poor core, while it was positively correlated with the percent of good core. Finally, the recommendation for minimum acceptable value of California bearing ratio (CBR) was provided based on the correlation between DPI and rate of change of rutting code. The recommendation enables the selection of a CBR value based on the number of years required for unit increase in the rutting code.

Suggested Citation

  • Dunja Perić & Gyuhyeong Goh & Javad Saeidaskari & Arash Saeidi Rashk Olia & Pooyan Ayar, 2022. "Development of Prediction Models for Performance of Flexible Pavements in Kansas with Emphasis on the Effects of Subgrade and Unbound Layers," Sustainability, MDPI, vol. 14(15), pages 1-21, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:9020-:d:869453
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    References listed on IDEAS

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    1. Ian T. Jolliffe, 1982. "A Note on the Use of Principal Components in Regression," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 31(3), pages 300-303, November.
    2. Madanat, Samer, 1993. "Incorporating inspection decisions in pavement management," Transportation Research Part B: Methodological, Elsevier, vol. 27(6), pages 425-438, December.
    3. Prozzi, J A & Madanat, S M, 2004. "Development of Pavement Performance Models by Combining Experimental and Field Data," University of California Transportation Center, Working Papers qt6cf8v5cw, University of California Transportation Center.
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