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Design of Frost Resistant Pavement Structure Based on Road Weather Stations (RWSs) Data

Author

Listed:
  • Audrius Vaitkus

    (Road Research Institute, Vilnius Gediminas Technical University, Linkmenų str. 28, Vilnius LT-08217, Lithuania)

  • Judita Gražulytė

    (Road Research Institute, Vilnius Gediminas Technical University, Linkmenų str. 28, Vilnius LT-08217, Lithuania)

  • Egidijus Skrodenis

    (Department of Urban Engineering, Vilnius Gediminas Technical University, Saulėtekio ave. 11, Vilnius LT-10223, Lithuania)

  • Igoris Kravcovas

    (Road Research Institute, Vilnius Gediminas Technical University, Linkmenų str. 28, Vilnius LT-08217, Lithuania)

Abstract

Frost is a decisive factor influencing pavement performance in cold countries. In the EU, millions of euros are spent annually on winter maintenance. About one-third of the maintenance budget is allocated to rehabilitation due to the negative impact of frost. The negative effect of frost is restricted by using non-frost-susceptible materials within the frost zone and regulating water accumulation. However, experience shows that the thickness of constructed pavement structure is often inadequate and that frost penetrates into the subgrade of frost-susceptible materials. The aim of this paper is to introduce the thickness calculation approach of the frost resistant pavement structure using road weather station (RWS) data. The subgrade susceptibility to frost and the number of equivalent single axle loads (ESALs) are considered as factors too. The calculated thickness of the frost resistant pavement structure is corrected according to the specific local conditions. After performing a statistical analysis of 2012–2014 data pertaining to 26 RWSs, Lithuania was divided into four regions according to the maximum frost depths, where the maximum values depending on RWS location varied from 110.4 cm to 179.1 cm.

Suggested Citation

  • Audrius Vaitkus & Judita Gražulytė & Egidijus Skrodenis & Igoris Kravcovas, 2016. "Design of Frost Resistant Pavement Structure Based on Road Weather Stations (RWSs) Data," Sustainability, MDPI, vol. 8(12), pages 1-13, December.
    • Handle: RePEc:gam:jsusta:v:8:y:2016:i:12:p:1328-:d:85404
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    Citations

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    Cited by:

    1. José Ángel Aranda & María Moncho Santonja & MÁ Gil Saurí & Guillermo Peris-Fajarnés, 2021. "Minimizing Shadow Area in Mountain Roads for Improving the Sustainability of Infrastructures," Sustainability, MDPI, vol. 13(10), pages 1-16, May.
    2. Qinglin Li & Haibin Wei & Peilei Zhou & Yangpeng Zhang & Leilei Han & Shuanye Han, 2019. "Experimental and Numerical Research on Utilizing Modified Silty Clay and Extruded Polystyrene (XPS) Board as the Subgrade Thermal Insulation Layer in a Seasonally Frozen Region, Northeast China," Sustainability, MDPI, vol. 11(13), pages 1-15, June.
    3. Junling Si & Tatsuya Ishikawa & Daoju Ren & Kimio Maruyama & Chigusa Ueno, 2023. "Response Prediction of Asphalt Pavement in Cold Region with Thermo-Hydro-Mechanical Coupling Simulation," Sustainability, MDPI, vol. 15(18), pages 1-29, September.
    4. Qinglin Li & Haibin Wei & Leilei Han & Fuyu Wang & Yangpeng Zhang & Shuanye Han, 2019. "Feasibility of Using Modified Silty Clay and Extruded Polystyrene (XPS) Board as the Subgrade Thermal Insulation Layer in a Seasonally Frozen Region, Northeast China," Sustainability, MDPI, vol. 11(3), pages 1-15, February.
    5. Martin Decky & Katarina Hodasova & Zuzana Papanova & Eva Remisova, 2022. "Sustainable Adaptive Cycle Pavements Using Composite Foam Concrete at High Altitudes in Central Europe," Sustainability, MDPI, vol. 14(15), pages 1-19, July.
    6. Hyun-Jun Choi & Sewon Kim & YoungSeok Kim & Jongmuk Won, 2022. "Predicting Frost Depth of Soils in South Korea Using Machine Learning Techniques," Sustainability, MDPI, vol. 14(15), pages 1-14, August.

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