From Particle Gradation to Soil Water Retention and Suction Stress Characteristic Curves of Sands Using the Unsaturated Discrete Spheres Method

The soil-water retention curve (SWRC) and suction stress characteristic curve (SSCC) are fundamental to understanding the hydromechanical behavior of unsaturated soils. However, direct laboratory measurement of these curves is often challenging due to cost, time, expertise, and equipment requirements. Therefore, previous studies have attempted to estimate the SWRC or SSCC through numerical or analytical methods, but these methods have limitations that restrict their accuracy and applicability, particularly regarding particle size variations. This study introduces a new method called the unsaturated discrete spheres method (UDSM) for determining the SWRC and SSCC of unsaturated sands based on particle gradation. Analytical equations are developed to calculate matric suction, volumetric water content, and suction stress for a two-particle system using soil particle gradation characteristics. These expressions are then extended to a representative particle assembly using the discrete element method (DEM). The proposed method’s accuracy is validated against experimental SWRC and SSCC data from 11 different sandy soils. Results show strong agreement between predicted and measured values, demonstrating that the UDSM can reliably capture the hydromechanical response of unsaturated sands. The UDSM offers a practical, physics-based, and scalable solution for estimating SWRC and SSCC when laboratory testing is not feasible, providing a valuable tool for geotechnical analysis and design involving unsaturated soils.

Authors

Institutions

Publication Details

Journal
Journal of Engineering Mechanics
Published
2026-04-02
DOI
https://doi.org/10.1061/jenmdt.emeng-8575
Primary Topic
Soil and Unsaturated Flow
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

From Particle Gradation to Soil Water Retention and Suction Stress Characteristic Curves of Sands Using the Unsaturated Discrete Spheres Method

Amir Akbari Garakani, Ali Pirjalili, Farshid Vahedifard, Mohammad Mohammadnia
Journal of Engineering Mechanics
Soil and Unsaturated Flow
article

From Particle Gradation to Soil Water Retention and Suction Stress Characteristic Curves of Sands Using the Unsaturated Discrete Spheres Method

Amir Akbari Garakani, Ali Pirjalili, Farshid Vahedifard, Mohammad Mohammadnia
article en

Abstract

The soil-water retention curve (SWRC) and suction stress characteristic curve (SSCC) are fundamental to understanding the hydromechanical behavior of unsaturated soils. However, direct laboratory measurement of these curves is often challenging due to cost, time, expertise, and equipment requirements. Therefore, previous studies have attempted to estimate the SWRC or SSCC through numerical or analytical methods, but these methods have limitations that restrict their accuracy and applicability, particularly regarding particle size variations. This study introduces a new method called the unsaturated discrete spheres method (UDSM) for determining the SWRC and SSCC of unsaturated sands based on particle gradation. Analytical equations are developed to calculate matric suction, volumetric water content, and suction stress for a two-particle system using soil particle gradation characteristics. These expressions are then extended to a representative particle assembly using the discrete element method (DEM). The proposed method’s accuracy is validated against experimental SWRC and SSCC data from 11 different sandy soils. Results show strong agreement between predicted and measured values, demonstrating that the UDSM can reliably capture the hydromechanical response of unsaturated sands. The UDSM offers a practical, physics-based, and scalable solution for estimating SWRC and SSCC when laboratory testing is not feasible, providing a valuable tool for geotechnical analysis and design involving unsaturated soils.

Journal of Engineering MechanicsVol. 152(6)
Tufts University (US), Sharif University of Technology (IR), UNSW Sydney (AU), Niroo Research Institute (IR)
Openalex Percentile: Top 25%
Soil and Unsaturated Flow
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.