A Non-Linear Suction-Dependent Model for Predicting Unsaturated Shear Strength

Accurate evaluation of unsaturated shear strength remains a significant challenge in geotechnical engineering because of the nonlinear interaction between matric suction and shear strength. Existing models often assume a linear contribution of suction and are generally restricted to low suction ranges, limiting their predictive capability under highly unsaturated conditions. This study investigated the nonlinear response of unsaturated shear strength through single-stage direct shear tests conducted under constant water content. Two soil types: a high-plasticity clay and a low-plasticity silty clay were examined across a wide suction range extending beyond the air-entry value (AEV). The results revealed a nonlinear behavior expressed as a distinct bi-linear trend, with shear strength increasing with suction up to the optimal moisture condition and then exhibiting a clearly altered rate of increase at higher suction levels. To capture this nonlinear behavior of unsaturated shear strength with suction, an exponential shear strength equation was proposed and validated using eight additional published datasets encompassing different soil classifications and suction magnitudes. The proposed formulation demonstrates that accounting for non-linearity is essential for accurately estimating the unsaturated shear strength of the soil. Moreover, the proposed exponential model outperforms both the well-established linear model of Fredlund and the nonlinear power law model of Abramento and Carvalho, thereby providing a unified framework for capturing the nonlinear interaction of matric suction on unsaturated shear strength.

Authors

Institutions

Publication Details

Journal
Geosciences
Published
2025-12-23
DOI
https://doi.org/10.3390/geosciences16010012
Primary Topic
Soil and Unsaturated Flow
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Non-Linear Suction-Dependent Model for Predicting Unsaturated Shear Strength

Kalani Rajamanthri, Claudia E. Zapata
Geosciences
Soil and Unsaturated Flow
article

A Non-Linear Suction-Dependent Model for Predicting Unsaturated Shear Strength

Kalani Rajamanthri, Claudia E. Zapata
article en

Abstract

Accurate evaluation of unsaturated shear strength remains a significant challenge in geotechnical engineering because of the nonlinear interaction between matric suction and shear strength. Existing models often assume a linear contribution of suction and are generally restricted to low suction ranges, limiting their predictive capability under highly unsaturated conditions. This study investigated the nonlinear response of unsaturated shear strength through single-stage direct shear tests conducted under constant water content. Two soil types: a high-plasticity clay and a low-plasticity silty clay were examined across a wide suction range extending beyond the air-entry value (AEV). The results revealed a nonlinear behavior expressed as a distinct bi-linear trend, with shear strength increasing with suction up to the optimal moisture condition and then exhibiting a clearly altered rate of increase at higher suction levels. To capture this nonlinear behavior of unsaturated shear strength with suction, an exponential shear strength equation was proposed and validated using eight additional published datasets encompassing different soil classifications and suction magnitudes. The proposed formulation demonstrates that accounting for non-linearity is essential for accurately estimating the unsaturated shear strength of the soil. Moreover, the proposed exponential model outperforms both the well-established linear model of Fredlund and the nonlinear power law model of Abramento and Carvalho, thereby providing a unified framework for capturing the nonlinear interaction of matric suction on unsaturated shear strength.

GeosciencesVol. 16(1)
Arizona State University (US)
U.S. Department of Transportation
Openalex Percentile: Top 37%
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.