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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

Author

Listed:
  • Qinglin Li

    (School of Transportation, Jilin University, Changchun 130022, China)

  • Haibin Wei

    (School of Transportation, Jilin University, Changchun 130022, China)

  • Peilei Zhou

    (School of Transportation, Jilin University, Changchun 130022, China)

  • Yangpeng Zhang

    (School of Transportation, Jilin University, Changchun 130022, China)

  • Leilei Han

    (School of Transportation, Jilin University, Changchun 130022, China)

  • Shuanye Han

    (School of Transportation, Jilin University, Changchun 130022, China)

Abstract

For strengthening sustainability of subgrade life-cycle service performance and storing industry solid wastes in seasonally frozen regions, compared to previous research of modified silty clay (MC) which consisted of oil shale ash (OSA), fly ash (FA), and silty clay (SC), we identified for the first time, the variations in the thermal insulation capability of MC with different levels of dry density and moisture content. Taking into consideration the effects of 0–20 freeze-thaw (F-T) cycles by a laboratory test, and by the numerical simulation of coupling moisture-temperature, while considering the effects of F-T cycles, the thermal insulation capability of the MC board and the XPS board were studied quantitatively. The testing results show that the thermal conductivity of MC and SC gradually decreases as the number of F-T cycles increases, and that of the XPS board increases with the increased number of F-T cycles, and tend to be of a constant value of 0.061 W/m/K after 17 F-T cycles. The specific heat capacity of the solid particles of the MC, SC, and XPS board does not change regularly as their moisture content, and the number of F-T cycles change, and their variations are in the range of the test error (2%). Simulation results show that MC has the advantage of the thermal insulation property to reduce the frost-depth of 0.21 m, and the thermal insulation property of the composite layer consisting of the MC and XPS board is greater to reduce the frost-depth of 0.55 m, so that it can protect both the SC and sand gravel of the experimental road from the frost heave damage. The research methods and results are very significant in accurately evaluating the thermal insulation capacity and the sustainability of MC and the composite layer consisting of the MC and XPS board, strengthening the stability of the subgrade and increasing the availability of industrial waste.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:13:p:3495-:d:242929
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    References listed on IDEAS

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    1. 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.
    2. 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.
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    Cited by:

    1. Haibin Wei & Qinglin Li & Leilei Han & Shuanye Han & Fuyu Wang & Yangpeng Zhang & Zhao Chen, 2019. "Experimental Research on Deformation Characteristics of Using Silty Clay Modified by Oil Shale Ash and Fly Ash as the Subgrade Material after Freeze-Thaw Cycles," Sustainability, MDPI, vol. 11(18), pages 1-19, September.
    2. 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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