Microstructural study of liquefaction in highly polydisperse granular media
Bibliographic record
Abstract
During earthquakes, rapid loading on loose, water-saturated silty sands can lead to undrained (constant volume) conditions that induce high pore water pressures. This process, known as liquefaction in geotechnical engineering, involves a loss of stress in the solid phase (effective) and can result in structural failures, such as frequent mine tailings dam collapses. Understanding the particle-scale mechanisms behind liquefaction is crucial for predictive modeling. However, this aspect remains poorly explored due to experimental limitations. In this study, we use discrete element method (DEM) simulations on one highly polydisperse granular material to investigate liquefaction. Samples of varying density are prepared by removing different amounts of floating particles (rattlers) after consolidation. The samples are then sheared under constant volume to the critical state. The results show that loose samples lose all strength, medium-loose samples temporarily liquefy but regain strength at large strains, and denser samples do not liquefy and exhibit continued shear strain hardening. At the micro-mechanical scale, permanent liquefaction is linked to heterogeneous solid fraction distributions (macropores), while samples with uniformly distributed local solid fraction either resist liquefaction or recover from it.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".