Exploring the tensorial nature of capillary stress and the constitutive role of contact stress in wet granular materials
Bibliographic record
Abstract
The current study adopts a micromechanical approach to explore the nature of stress transmission in wet granular materials. First, we derive the discrete form of the capillary stress tensor obtained from homogenization to show the virial nature of capillarity through the application of point-wise capillary forces in Discrete Element Modeling (DEM). Furthermore, the non-spherical character of the capillary stress tensor is highlighted through a series of DEM triaxial simulations. Contrary to common thinking, the capillary stress tensor has indeed both mean and deviatoric components due to the underlying micromechanical aspects. Relevant key dimensionless parameters are identified to evaluate the relative magnitude of the capillary stress to the externally applied and contact (intergranular) stresses, thus determining the specific conditions under which the contribution of the deviatoric part becomes considerable. In addition, a DEM simulation of a simple shear test is performed to confirm the anisotropy (non-sphericity) of capillary stress tensor. Finally, the effective nature of the contact stress in the sense of Terzaghi for the constitutive behavior of wet granular materials is investigated via a DEM stress probing analysis. Results suggest that a single contact stress variable – germane to an effective stress – cannot relate to strain for the constitutive law in triphasic condition. • Capillary stress is virial through point-wise intergranular capillary forces in DEM. • The non-spherical nature of the capillary stress tensor is formally demonstrated. • A p -constant shear test reveals the existence of purely deviatoric capillary stress. • Capillary stress is more deviatoric at higher suctions and lower confining stresses. • The contact stress cannot play the role of an effective stress for wet materials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".