Issue |
MATEC Web Conf.
Volume 337, 2021
PanAm-Unsat 2021: 3rd Pan-American Conference on Unsaturated Soils
|
|
---|---|---|
Article Number | 02001 | |
Number of page(s) | 8 | |
Section | Constitutive and Numerical Modeling | |
DOI | https://doi.org/10.1051/matecconf/202133702001 | |
Published online | 26 April 2021 |
Modelling of soil-water retention curve considering the effects of existing salt solution in the pore fluid
1 Assistant Professor, Department of Civil Engineering, Sharif University of Technology, Tehran, Iran
2 M.Sc. Student, Department of Civil Engineering, Sharif University of Technology, Tehran, Iran.
* Corresponding author: hsadeghi@sharif.edu
Soil-water retention curve (SWRC) has a wide application in geoenvironmental engineering from the predication of unsaturated shear strength to transient two-phase flow and stability analyses. Although various SWRC models have been proposed to take into account some influencing factors, less attention has been given to consider the effects of pore fluid osmotic potential. Therefore, the key objective of this study is to extend van Genchten’s model so that osmotic potential is considered as an independent factor governing the SWRC behavior. The new model comprises only six variables, which can be calibrated through minimal experimental measurements. More importantly, most of the model parameters have physical meaning by correlating macroscopic volumetric behavior and general trends of SWRC to osmotic potential. The results of validation tests revealed that the new osmotic-dependent SWRC model can predict the retention data in terms of both total and matric suction for two different soils and various molar concentrations very good. The proposed modeling approach does not require any advanced mercury intrusion porosimetry (MIP) tests, yet it can deliver excellent predictions by calibrating only six parameters which are far less than those incorporated into similar models for saline water permeating through the pore structure.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.