Geomechanics and Engineering

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A simplified directly determination of soil-water retention curve from pore size distribution

  • Niu, Geng (State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology) ;
  • Shao, Longtan (State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology) ;
  • Sun, De'an (Department of Civil Engineering, Shanghai University) ;
  • Guo, Xiaoxia (State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology)
  • Received : 2019.11.04
  • Accepted : 2020.02.06
  • Published : 2020.03.10
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Abstract

Numbers fitting-curve equations have been proposed to predict soil-water retention curve (SWRC) whose parameters have no definitude physical meaning. And these methods with precondition of measuring SWRC data is time-consuming. A simplified directly method to estimate SWRC without parameters obtained by fitting-curve is proposed. Firstly, the total SWRC can be discretized into linear segments respectively. Every segment can be represented by linear formulation and every turning point can be determined by the pore-size distribution (PSD) of Mercury Intrusion Porosimetry (MIP) tests. The pore diameters governing the air-entry condition (AEC) and residual condition (RC) can be determined by the PSDs of MIP test. The PSD changes significantly during drying in SWR test, so the determination of AEC and RC should use the PSD under corresponding suction conditions. Every parameter in proposed equations can be determined directly by PSD without curve-fitting procedure and has definitude physical meaning. The proposed equations give a good estimation of both unimodal and bimodal SWRCs.

Keywords

Acknowledgement

Supported by : National Natural Science Foundation of China, National Natural Science Foundation of Liaoning

This study was financially supported by National Key Laboratory Funding of Independent Research Project [grant number S18406]; National Natural Science Foundation of China [grant number 51479023, grant number 51909241], and National Natural Science Foundation of Liaoning [grant number 2019-ZD-0187].

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