The resilient moduli of five Canadian soils under wetting and freeze-thaw conditions and their estimation by using an artificial neural network model
The resilient modulus (MR) is a key parameter used in the mechanistic-empirical methods for the rational design of pavement structures. In permafrost and seasonally frozen regions, the MR of subgrade soils is significantly influenced by the variations in moisture content and temperature. The MR typi...
Gespeichert in:
Veröffentlicht in: | Cold regions science and technology 2019-12, Vol.168, p.102894, Article 102894 |
---|---|
Hauptverfasser: | , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | The resilient modulus (MR) is a key parameter used in the mechanistic-empirical methods for the rational design of pavement structures. In permafrost and seasonally frozen regions, the MR of subgrade soils is significantly influenced by the variations in moisture content and temperature. The MR typically reduces due to the weathering action associated with wetting and freeze-thaw (F-T) cycles, which contributes to the reorientation of soil particles, loss in suction and cohesion, and formation of cracks in the subgrade soils. In the present study, the MR values of five Canadian soils that are widely used as pavement subgrades were determined under wetting and F-T conditions. The key findings from the extensive experimental investigation suggest: (i) the MR values of the soils at their respective optimum water contents significantly reduce up to the critical F-T cycle, which is typically the first or second F-T cycles; (ii) there is little change in the MR values from the critical to the tenth F-T cycle; (iii) the percentage of reduction in the measured MR at the optimum water content after the critical F-T cycle is strongly related to the soils plasticity index; (iv) the measured MR values are typically low for the specimens subjected to wetting, and the effect of F-T cycles on these specimens is insignificant; and (v) the effect of stress levels on the MR values is dependent on the initial water contents of the specimens and soil types. In addition, an artificial neural network (ANN) model was proposed and validated for estimating the MR of the tested soils taking account of various influencing factors. Both the experimental data and the developed ANN model provide valuable information for the rational design of pavements in Canada.
•The MR of four soils tested decrease significantly after first or second F-T cycles.•The reduction in MR at the optimum water content is related to the plasticity index.•The effect of F-T cycles is insignificant when the specimens have high water contents.•The effect of stress levels is dependent on initial water contents and soil types. |
---|---|
ISSN: | 0165-232X 1872-7441 |
DOI: | 10.1016/j.coldregions.2019.102894 |