›› 2018, Vol. 39 ›› Issue (2): 598-604.doi: 10.16285/j.rsm.2017.1851

• Fundamental Theroy and Experimental Research • Previous Articles     Next Articles

Hysteresis model of soil-water characteristic curve

LI Cheng-sheng1, 2, KONG Ling-wei1, 2, BAI Wei1, AN Ran1, 2, LI Tian-guo1, 2   

  1. 1. State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan, Hubei 430071, China; 2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2017-09-11 Online:2018-02-10 Published:2018-06-06
  • Supported by:

    This work was supported by the National Natural Science Foundation of China (11672320, 41372314).

Abstract: Based on the Young-Laplace equation, the relationship between pore size distribution and soil-water characteristic curve is estimated. The lagging model of soil-water characteristic curve is established by referring to the statistical model of unsaturated seepage. The capillary water corresponding to the upper limit of the capillary radius under a certain suction of the substrate has a blocking effect on the capillary water of larger pore radius. The probability of obstruction is directly related to the pore distribution function. The pore size distribution function reflects the heterogeneity of spatial distribution of soil pores. The model shows that the desorption curve is almost identical to the absorption curve when the substrate is in high or low matric suction. The water content in the middle section of desorption is higher than that of the absorption curve, and there is a clear peak. The results show that the model works well for medium and fine granular soil, but the sandy soil porosity is beyond the model hypothesis and resulting large errors. For sandy soils, the introduction of blocking rate correction coefficient shows that the best correction factor and SWCC half log under the SWCC maximum slope inversely proportional relationship.

Key words: soil-water characteristic curve(SWCC), hysteresis, blocking probability, model

CLC Number: 

  • TU 43

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