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Determining the Bimodal Soil–Water Characteristic Curve of Fine-Grained Subgrade Soil Derived from the Compaction Condition by Incorporating Pore Size Distribution

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  • معلومة اضافية
    • بيانات النشر:
      MDPI AG
    • الموضوع:
      2023
    • Collection:
      Directory of Open Access Journals: DOAJ Articles
    • نبذة مختصرة :
      The soil–water characteristic curve (SWCC) is a key constitutive relationship for unsaturated soil which can be unimodal or bimodal. For the fine-grained compacted subgrade soil with a bimodal pattern, the determination of SWCC is complicated and needs a wide-range suction measurement. In this paper, the bimodal SWCC of a subgrade soil derived from the compaction condition was measured and determined by incorporating pore size distribution. For this purpose, a series of laboratory tests were conducted, including the pressure plate method, filter paper method, and vapor equilibrium method, which were used to measure SWCC at the low, medium, and high suction range, respectively. The pore size distribution (PSD) data were obtained by mercury intrusion porosimetry (MIP) tests and used to predict SWCC. Based on the analysis of hydraulic paths and SWCC-PSD correlations, the SWCC of the subgrade soil should be determined to follow the actual hydraulic path. SWCC within a low suction range can be filled by PSD-based data to improve the fitting accuracy. Then, a graphical method is applied to predict the bimodal SWCC by combining the filter paper method, vapor equilibrium method, and PSD-based data. The prediction curves fit well with the test data for all selected compaction conditions. Furthermore, the prediction method can still provide good prediction performance in the absence of high suction section data, which is beneficial for the application of bimodal SWCC.
    • ISSN:
      2227-9717
    • Relation:
      https://www.mdpi.com/2227-9717/11/12/3394; https://doaj.org/toc/2227-9717; https://doaj.org/article/13ce9bd4c68e48ad83e7d7edb2cdce01
    • الرقم المعرف:
      10.3390/pr11123394
    • الرقم المعرف:
      edsbas.5AF4822