A micromechanical model for predicting the dynamic properties of loose dry sands subjected to cyclic loading using DMA test

Conference Paper (2026)
Author(s)

Bernardo Caicedo (Universidad de Los Andes)

María Juliana Chaparro (Universidad de Los Andes)

Juan-Pablo Castillo-Betancourt (Universidad de Los Andes)

Miguel Cabrera (TU Delft - Civil Engineering & Geosciences)

Pierre Delage (Ecole des Ponts ParisTech (ENPC))

Research Group
Geo-engineering
DOI related publication
https://doi.org/10.53243/ICSMGE2026-1908 Final published version
More Info
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Publication Year
2026
Language
English
Research Group
Geo-engineering
Article number
1908
Pages (from-to)
1625-1628
Publisher
ÖGG
ISBN (print)
978-3-9503898-4-5
Event
21st International Conference on Soil Mechanics and Geotechnical Engineering 2026 (2026-06-14 - 2026-06-19), Austria Center Vienna, Vienna, Austria
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Abstract

Cyclic loading is characterized by load patterns applied at specific frequencies. It arises from natural events, such as seismic activity, which generates wave propagation through the soil and induces cyclic shearing. Under such conditions, contact forces between soil grains may shift and rearrange, allowing grain movement that can generate irreversible deformations. The dynamic response of soil deposits is primarily governed by the shear dynamic modulus G, the damping ratio ξ, and soil density ρ. This research focuses on the dynamic properties G and ξ of loose dry sand deposits, where low-density ρ and high void ratios e enhance particle sliding and rearrangement. This research aims to improve the understanding of the dynamic properties of loose dry sands by analyzing the degradation of G under cyclic loading. A novel micromechanical model based on Hertz–Mindlin theory is employed to simulate shear modulus degradation, explicitly incorporating particle roughness and contact interactions. Experimental data from shear rheometer tests on loose, dry sands are used to validate the model. The results show good agreement between experimental observations and model predictions, including very low confining pressures (≤ 10 kPa), highlighting the model’s robustness and versatility.

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