Liquefaction of crushable granular media: A multiscale numerical analysis
Bibliographic record
Abstract
Understanding liquefaction—the loss of shear resistance in granular materials under constantvolume shearing—is crucial for preventing landslides and geotechnical failures. This phenomenon typically occurs in water-saturated media during rapid undrained loading, such as seismic shocks. Liquefaction potential decreases with higher solid fraction and particle size polydispersity, but evolves if particle fragmentation occurs. We investigate the mechanics and microstructure of crushable, liquefiable granular materials through 2D undrained shear simulations. Results show that higher solid fractions and stronger particles delay liquefaction. Mechanical instabilities manifest as sharp drops in mean and deviatoric stresses, leading to resistance loss and fluid-like behavior. The redundancy number strongly correlates with shear resistance and contact network stability. At high solid fractions, grading upon fragmentation asymptotically approaches an ultimate state while maintaining stability. In contrast, looser samples exhibit earlier liquefaction, with fragmentation depending on particle strength. These findings highlight the critical role of particle strength in either mitigating or intensifying liquefaction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".