Inicio  /  Infrastructures  /  Vol: 8 Par: 2 (2023)  /  Artículo
ARTÍCULO
TITULO

Predictive Stress Modeling of Resilient Modulus in Sandy Subgrade Soils

Tadas Tamo?iunas and ?arunas Skuodis    

Resumen

The mechanical properties of pavement materials are crucial to the design and performance of flexible pavements. One of the most commonly used measures of these properties is the resilient modulus (Er). Many different models were developed to predict the resilient modulus of coarse soils, which are based on the states of stresses and the physical and mechanical properties of the soil. The unconsolidated unsaturated drained cyclic triaxial tests were performed for three variously graded and three well-graded sand specimens to determine the resilient modulus, and to perform predictive modeling using the K-?, Rahim and George, Uzan, and Universal Witczak models. Obtained Er values directly depended on the confining pressure and deviatoric stress values used during the test. The Octahedral Shear Stress (OSS) model, proposed by the authors of the paper, predicts the resilient modulus with a coefficient of determination (R2) ranging from 0.85 to 0.99. The advantage of the model is the use of small-scale data tables, meaning fixed K1 and K2 regression coefficients, and it can be assigned to a specific specimen type without the need to determine them using the specific deviatoric and confining stresses.

 Artículos similares

       
 
Giulia Grottesi, Guilherme B. A. Coelho and Dimitrios Kraniotis    
In the world of cultural heritage, a wide range of artefacts and buildings are made of wood and, therefore, are subjected to moisture-induced stress and strain cycles, owing to environmental fluctuations. Simultaneous action of moisture and mechanical lo... ver más
Revista: Applied Sciences

 
Geonwoo Kim, Hoonsoo Lee, Seung Hwan Wi and Byoung-Kwan Cho    
Heat stress in particular can damage physiological processes, adaptation, cellular homeostasis, and yield of higher plants. Early detection of heat stress in leafy crops is critical for preventing extensive loss of crop productivity for global food secur... ver más
Revista: Applied Sciences

 
Michael Lo, Saravanan Karuppanan and Mark Ovinis    
Machine learning tools are increasingly adopted in various industries because of their excellent predictive capability, with high precision and high accuracy. In this work, analytical equations to predict the failure pressure of a corroded pipeline with ... ver más

 
Valeriy Gornyakov, Yongle Sun, Jialuo Ding and Stewart Williams    
High pressure multi-layer rolling is an effective method to reduce residual stress and distortion in metallic components built by wire arc additive manufacturing (WAAM). However, the mechanisms of the reduction in residual stress and distortion during mu... ver más
Revista: Applied Sciences

 
Kristian Gundersen, Guttorm Alendal, Anna Oleynik and Nello Blaser    
The world?s oceans are under stress from climate change, acidification and other human activities, and the UN has declared 2021?2030 as the decade for marine science. To monitor the marine waters, with the purpose of detecting discharges of tracers from ... ver más
Revista: Algorithms