Micromechanical modeling of triphasic granular media
Bibliographic record
Abstract
This paper presents pore unit assembly-discrete element model (PUA-DEM), a pore-scale hydromechanical framework that resolves interactions between mobile granular particles and multiphase fluids in unsaturated granular media. The framework uniquely integrates DEM with pore-scale hydrodynamic models to capture unsaturated flow dynamics, while leveraging a two-way coupling mechanism to ensure bidirectional fluid-grain feedback through stabilized domain partitioning. Further innovations include a dynamic pore-merging and retriangulation algorithm that enhances computational efficiency for large-scale systems. Validated against experimental data for glass beads and Ottawa sand, PUA-DEM accurately reproduces critical hydromechanical phenomena-including capillary/viscous fingering, wetting-induced granular swelling/collapse, and quasi-static deformation-under diverse saturation and loading regimes. Numerical case studies reveal how capillary forces and wetting fluid saturation collectively govern granular response, from pore-scale meniscus evolution to macroscale flow instabilities. By bridging pore- and particle-scale physics, PUA-DEM advances predictive modeling of partially saturated granular systems, offering transformative insights for geohazard mitigation, sustainable agriculture, pharmaceutical manufacturing, and energy-related engineering applications.
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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 | 0.001 |
| 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".