MACRO- AND MICRO-BEHAVIORS OF SOIL WITH SOLUBLE PARTICLES DURING 1D COMPRESSIONAL TESTS USING 3D DEM SIMULATION
Bibliographic record
Abstract
Micro- and macro-behaviors of soils are significantly affected by soluble particles such as salts. To investigate the macro- and micro-behaviors of soil specimens with soluble particles, this study adopted the discrete element method to model a conventional one- imensional compression test (oedometer) for a sample of 10% salt. Salt particles are created to be softer compared to sand particles. The 3D discrete element method model was validated by laboratory experimental results carried out in a previous study. The oedometer was conducted by applying loads from 5kPa to 640 kPa. Macro- and microbehaviors of the specimen were investigated by observing several parameters, including vertical strain, porosity, vertical and horizontal stress, and contact force during compression. The simulation results showed that the 3D discrete element method model approximately relocated laboratory experimental results, with a high correlation to vertical strain and void ratio. The lateral earth pressure ratio continuously decreased during loading. Moreover, observation of the force chain during loading revealed a rearrangement of soil particles and enhancement of inter-particlecontacts. The macro- and micro-behaviors of soil with soluble particles could be effectively investigated using the 3D discrete element method model. The model provided a reliable framework for capturing the macro- and micro-mechanical properties of granular mixtures with soluble grains under confined compression. However, the dissolution of the sample was not implemented. Future research could focus on the dissolution phenomenon in the 3D discrete element method model to provide a deeper understanding of soluble particles on soil behaviors, particularly under changing environmental conditions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".