scholarly journals Influence of drying–wetting cycles on soil-water characteristic curve of undisturbed granite residual soils and microstructure mechanism by nuclear magnetic resonance (NMR) spin-spin relaxation time (T2) relaxometry

2018 ◽  
Vol 55 (2) ◽  
pp. 208-216 ◽  
Author(s):  
Lingwei Kong ◽  
Hossain Md. Sayem ◽  
Huihui Tian

Due to the formational environment and climatic variability, granite residual soils with grain-size distribution ranging from gravel to clay undergo multiple drying–wetting cycles. The influences of multiple drying–wetting cycles on the soil-water characteristic curve (SWCC) and pore-size distribution (POSD) of undisturbed granite residual soils are investigated using the pressure plate test and nuclear magnetic resonance (NMR) spin-spin relaxation time (T2) distribution measurement, respectively. Results show that the water-retention capacity and air-entry value decrease and pores become more uniform with increasing drying–wetting cycles. After four drying–wetting cycles, the soil reaches a nearly constant state. The POSD change of multiple drying–wetting cycle samples is consistent with the SWCC of the soils. Furthermore, a modified van Genuchten model in terms of cumulative pore volume is used to obtain the best-fit POSD of the drying–wetting cycle samples. The shape and changing tendency of both curves of SWCC and POSD are quite similar and achieved a better correlation. It can be concluded that the SWCC is strongly dependent on the POSD of the soil and NMR T2 relaxometry can be used as an alternative to the assessment of microstructural variation of residual soils subjected to the periodic drying and wetting process.

1994 ◽  
Vol 31 (4) ◽  
pp. 521-532 ◽  
Author(s):  
D.G. Fredlund ◽  
Anqing Xing

The soil-water characteristic curve can be used to estimate various parameters used to describe unsaturated soil behaviour. A general equation for the soil-water characteristic curve is proposed. A nonlinear, least-squares computer program is used to determine the best-fit parameters for experimental data presented in the literature. The equation is based on the assumption that the shape of the soil-water characteristic curve is dependent upon the pore-size distribution of the soil (i.e., the desaturation is a function of the pore-size distribution). The equation has the form of an integrated frequency distribution curve. The equation provides a good fit for sand, silt, and clay soils over the entire suction range from 0 to 106 kPa. Key words : soil-water characteristic curve, pore-size distribution, nonlinear curve fitting, soil suction, water content.


1994 ◽  
Vol 26 (Supplement) ◽  
pp. S194
Author(s):  
G. Yue ◽  
A. L. Alexander ◽  
D. H. Laidlaw ◽  
A. F. Gmitro ◽  
E. C. Unger ◽  
...  

2020 ◽  
Vol 195 ◽  
pp. 02024
Author(s):  
Roberto Dutra Alves ◽  
Gilson de F. N. Gitirana ◽  
Sai K. Vanapalli

The development of theoretical and semi-empirical models to study capillary mechanisms and predict the soil-water characteristic curve (SWCC) generally requires the idealization of pore space and pore water, considering simplifying hypotheses. The study of ideal materials comprised of particles with controlled shape and size allows the evaluation of such simplifying hypotheses and the subsequent generalization to actual soils. In this paper, four theoretical and semi-empirical models for the prediction of the SWCC are applied to the prediction of artificial materials comprised of spherical particles. Nineteen grain-size distribution curves, with varying coefficients of uniformity are considered. The dataset is comprised of materials previously published and additional tests carried out by the authors, under highly controlled conditions. The analyses allowed the evaluation of the effect of grain-size distribution curve and shape of the particles. The limitations and advantages of each prediction model was investigated, and a detailed comparison is presented, guiding future implementations of improved models.


2021 ◽  
Vol 337 ◽  
pp. 02012
Author(s):  
Wei Yan ◽  
Emanuel Birle ◽  
Roberto Cudmani

The soil water characteristic curve (SWCC) of soils can be derived from the measured pore size distribution (PSD) data by applying capillary models. This method is limited for clayey soils due to the PSD changes during SWCC testing. In this study, a suction-dependent multimodal PSD model based on probability theory is developed and used to derive SWCC. The model is validated by simulating the drying branches of SWCCs of four compacted Lias Clay samples with different initial states. A good consistency between the measured and predicted SWCC is shown.


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