Research Article

Critical State Response of Granular Soils: Probabilistic Predictive Models Incorporating Grain Size, Distribution and Shape Effects

Number: Advanced Online Publication Early Pub Date: October 5, 2026
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Critical State Response of Granular Soils: Probabilistic Predictive Models Incorporating Grain Size, Distribution and Shape Effects

Abstract

The critical state locus (CSL), expressed in the void ratio (e) – natural logarithmic mean effective stress (ln⁡p') space, is typically defined by slope (λ_e) and intercept parameters (Γ_1), the latter corresponding to the void ratio at a reference mean effective stress of unity. The angle of shearing resistance at the critical state (ϕ_cs^') relates the shear strength to effective normal stresses. These parameters are fundamentally governed by intrinsic properties of granular soils. This study examines their dependence on particle-scale descriptors, namely median grain size (D_50), coefficient of uniformity (C_u), particle roundness (R), and sphericity (S). A database containing critical state parameters (CSP), and grain size, gradation, and shape descriptors for over two hundred sandy and silty non-plastic soils was compiled from available literature, supplemented with laboratory tests performed on Cine, Sile, Tekirdag, and Iskenderun silica sands from Turkiye, and Sabratha silt from Libya. Their CSPs were evaluated following the procedures outlined by Santamarina and Cho [1], modified by benefiting from photogrammetric techniques for monitoring the specimen volume. Particle roundness and sphericity were quantified from microscopic imaging using the method defined by Cho et al. [2]. Semi-empirical probabilistic predictive models were developed using a maximum-likelihood estimation framework. They suggest that ϕ_cs^' decreases with increasing R, decreasing C_u, but log-linearly increases with increasing D_50. The intercept Γ_1 decreases linearly with increasing R and decreasing S and C_u, and exhibits a log-linear decrease with increasing D_50. The compressibility λ_e increases with increasing D_50, whereas it decreases with better grading. It exhibits a log-linear decrease with increasing R and S. The model performances, evaluated through analyses of residuals, indicate unbiased predictions with well-quantified levels of model precision. The resulting models provide quantitative insight into the relationships between micro-scale particle characteristics and macro-scale critical state behavior. They offer practical means for preliminary estimation of CSPs by explicitly incorporating variability in grain size, gradation, and shape metrics of granular soils.

Keywords

References

  1. Santamarina, J., Cho, G., 2001. Determination of Critical State Parameters in Sandy Soils—Simple Procedure. Geotech. Test. J. 24, 185–192. https://doi.org/10.1520/GTJ11338J
  2. Cho, G.-C., Dodds, J., Santamarina, J.C., 2006. Particle Shape Effects on Packing Density, Stiffness, and Strength: Natural and Crushed Sands. J. Geotech. Geoenvironmental Eng. 132, 591–602. https://doi.org/10.1061/(ASCE)1090-0241(2006)132:5(591)
  3. Bareither, C.A., Edil, T.B., Benson, C.H., Mickelson, D.M., 2008. Geological and Physical Factors Affecting the Friction Angle of Compacted Sands. J. Geotech. Geoenvironmental Eng. 134, 1476–1489. https://doi.org/10.1061/(ASCE)1090-0241(2008)134:10(1476)
  4. Cavarretta, I., O’Sullivan, C., Coop, M.R., 2017. The relevance of roundness to the crushing strength of granular materials. Géotechnique 67, 301–312. https://doi.org/10.1680/jgeot.15.P.226
  5. He, H., Zheng, J., 2020. Simulations of realistic granular soils in oedometer tests using physics engine. Int. J. Numer. Anal. Methods Geomech. 44, 983–1002. https://doi.org/10.1002/nag.3031
  6. Koerner, R.M., 1969. Limiting density behavior of quartz powders. Powder Technol. 3, 208–212. https://doi.org/10.1016/0032-5910(69)80079-3
  7. Mitchell, J.K., Soga, K., 2005. Fundamentals of Soil Behavior, 3rd ed. John Wiley & Sons, Inc.
  8. Santamarina, C., Cascante, G., 1998. Effect of surface roughness on wave propagation parameters. Géotechnique 48, 129–136. https://doi.org/10.1680/geot.1998.48.1.129

Details

Primary Language

English

Subjects

Civil Geotechnical Engineering, Soil Mechanics in Civil Engineering

Journal Section

Research Article

Early Pub Date

October 5, 2026

Publication Date

-

Submission Date

April 30, 2026

Acceptance Date

October 1, 2026

Published in Issue

Year 2026 Number: Advanced Online Publication

APA
Çetin, K. Ö., Çakır, E., & Aksoy, A. S. (2026). Critical State Response of Granular Soils: Probabilistic Predictive Models Incorporating Grain Size, Distribution and Shape Effects. Turkish Journal of Civil Engineering, Advanced Online Publication. https://doi.org/10.18400/tjce.1935102
AMA
1.Çetin KÖ, Çakır E, Aksoy AS. Critical State Response of Granular Soils: Probabilistic Predictive Models Incorporating Grain Size, Distribution and Shape Effects. TJCE. 2026;(Advanced Online Publication). doi:10.18400/tjce.1935102
Chicago
Çetin, Kemal Önder, Elife Çakır, and Ahmet Seyit Aksoy. 2026. “Critical State Response of Granular Soils: Probabilistic Predictive Models Incorporating Grain Size, Distribution and Shape Effects”. Turkish Journal of Civil Engineering, no. Advanced Online Publication. https://doi.org/10.18400/tjce.1935102.
EndNote
Çetin KÖ, Çakır E, Aksoy AS (October 1, 2026) Critical State Response of Granular Soils: Probabilistic Predictive Models Incorporating Grain Size, Distribution and Shape Effects. Turkish Journal of Civil Engineering Advanced Online Publication
IEEE
[1]K. Ö. Çetin, E. Çakır, and A. S. Aksoy, “Critical State Response of Granular Soils: Probabilistic Predictive Models Incorporating Grain Size, Distribution and Shape Effects”, TJCE, no. Advanced Online Publication, Oct. 2026, doi: 10.18400/tjce.1935102.
ISNAD
Çetin, Kemal Önder - Çakır, Elife - Aksoy, Ahmet Seyit. “Critical State Response of Granular Soils: Probabilistic Predictive Models Incorporating Grain Size, Distribution and Shape Effects”. Turkish Journal of Civil Engineering. Advanced Online Publication (October 1, 2026). https://doi.org/10.18400/tjce.1935102.
JAMA
1.Çetin KÖ, Çakır E, Aksoy AS. Critical State Response of Granular Soils: Probabilistic Predictive Models Incorporating Grain Size, Distribution and Shape Effects. TJCE. 2026. doi:10.18400/tjce.1935102.
MLA
Çetin, Kemal Önder, et al. “Critical State Response of Granular Soils: Probabilistic Predictive Models Incorporating Grain Size, Distribution and Shape Effects”. Turkish Journal of Civil Engineering, no. Advanced Online Publication, Oct. 2026, doi:10.18400/tjce.1935102.
Vancouver
1.Kemal Önder Çetin, Elife Çakır, Ahmet Seyit Aksoy. Critical State Response of Granular Soils: Probabilistic Predictive Models Incorporating Grain Size, Distribution and Shape Effects. TJCE. 2026 Oct. 1;(Advanced Online Publication). doi:10.18400/tjce.1935102