Use of Linear Extrapolation to Estimate Critical State Void Ratio from Drained Triaxial Shear Tests on Dense Cohesionless Soil
Within the strain level attainable in drained triaxial tests, it is not uncommon for dense cohesionless soil to be sheared insufficiently to reach the critical state. Linear fitting of the correlative data from the maximum stress ratio or minimum dilatancy to the end of the test, and then extrapolat...
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MDPI AG
2024-01-01
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| Online Access: | https://www.mdpi.com/2076-3417/14/2/694 |
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| author | Haifeng Zhang Guohui Lei |
| author_facet | Haifeng Zhang Guohui Lei |
| author_sort | Haifeng Zhang |
| collection | DOAJ |
| description | Within the strain level attainable in drained triaxial tests, it is not uncommon for dense cohesionless soil to be sheared insufficiently to reach the critical state. Linear fitting of the correlative data from the maximum stress ratio or minimum dilatancy to the end of the test, and then extrapolating these fitted lines to the critical stress ratio or zero dilatancy has been frequently used to estimate the critical state void ratio. However, the linear extrapolation method is empirical and involves different choices of correlative test data, which leads to different estimates. Therefore, a series of simulations of drained tests on dense Toyoura sand are performed using a state-dependent model. Multiple data sets are generated, including void ratio <i>e</i>, volumetric strain <i>ε<sub>v</sub></i>, stress ratio <i>η</i>, and dilatancy <i>D</i>. The linear extrapolation accuracy of the <i>e</i>–<i>η</i>, <i>e</i>–<i>D</i>, and <i>ε<sub>v</sub></i>–<i>D</i> data sets is examined. It turns out that the <i>e</i>–<i>η</i> data set is best suited. The goodness of the <i>e</i>–<i>η</i> data set is examined against 18 sets of experimental data on dense sand. In addition, the selection of the start point for extrapolation is shown to influence the estimates. The latter 50% of the post-peak data is found to be reliable. |
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| language | English |
| last_indexed | 2024-03-08T09:58:41Z |
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| spelling | doaj.art-47f3d500fb4a4b39953169bafebdb1c52024-01-29T13:43:45ZengMDPI AGApplied Sciences2076-34172024-01-0114269410.3390/app14020694Use of Linear Extrapolation to Estimate Critical State Void Ratio from Drained Triaxial Shear Tests on Dense Cohesionless SoilHaifeng Zhang0Guohui Lei1Key Laboratory of Geomechanics and Embankment Engineering of the Ministry of Education, Geotechnical Research Institute, Hohai University, 1 Xikang Road, Nanjing 210024, ChinaKey Laboratory of Geomechanics and Embankment Engineering of the Ministry of Education, Geotechnical Research Institute, Hohai University, 1 Xikang Road, Nanjing 210024, ChinaWithin the strain level attainable in drained triaxial tests, it is not uncommon for dense cohesionless soil to be sheared insufficiently to reach the critical state. Linear fitting of the correlative data from the maximum stress ratio or minimum dilatancy to the end of the test, and then extrapolating these fitted lines to the critical stress ratio or zero dilatancy has been frequently used to estimate the critical state void ratio. However, the linear extrapolation method is empirical and involves different choices of correlative test data, which leads to different estimates. Therefore, a series of simulations of drained tests on dense Toyoura sand are performed using a state-dependent model. Multiple data sets are generated, including void ratio <i>e</i>, volumetric strain <i>ε<sub>v</sub></i>, stress ratio <i>η</i>, and dilatancy <i>D</i>. The linear extrapolation accuracy of the <i>e</i>–<i>η</i>, <i>e</i>–<i>D</i>, and <i>ε<sub>v</sub></i>–<i>D</i> data sets is examined. It turns out that the <i>e</i>–<i>η</i> data set is best suited. The goodness of the <i>e</i>–<i>η</i> data set is examined against 18 sets of experimental data on dense sand. In addition, the selection of the start point for extrapolation is shown to influence the estimates. The latter 50% of the post-peak data is found to be reliable.https://www.mdpi.com/2076-3417/14/2/694critical statevoid ratiostress ratiodilatancylinear extrapolation |
| spellingShingle | Haifeng Zhang Guohui Lei Use of Linear Extrapolation to Estimate Critical State Void Ratio from Drained Triaxial Shear Tests on Dense Cohesionless Soil Applied Sciences critical state void ratio stress ratio dilatancy linear extrapolation |
| title | Use of Linear Extrapolation to Estimate Critical State Void Ratio from Drained Triaxial Shear Tests on Dense Cohesionless Soil |
| title_full | Use of Linear Extrapolation to Estimate Critical State Void Ratio from Drained Triaxial Shear Tests on Dense Cohesionless Soil |
| title_fullStr | Use of Linear Extrapolation to Estimate Critical State Void Ratio from Drained Triaxial Shear Tests on Dense Cohesionless Soil |
| title_full_unstemmed | Use of Linear Extrapolation to Estimate Critical State Void Ratio from Drained Triaxial Shear Tests on Dense Cohesionless Soil |
| title_short | Use of Linear Extrapolation to Estimate Critical State Void Ratio from Drained Triaxial Shear Tests on Dense Cohesionless Soil |
| title_sort | use of linear extrapolation to estimate critical state void ratio from drained triaxial shear tests on dense cohesionless soil |
| topic | critical state void ratio stress ratio dilatancy linear extrapolation |
| url | https://www.mdpi.com/2076-3417/14/2/694 |
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