Upward migration of soil particles induced by the sloshing of slurries under cyclic load: experiments and theoretical explanation
Bibliographic record
Abstract
Internal stability of subgrade soil under dynamic train loads plays an essential role in the serviceability of rail embankments. “Mud pumping”, the upward migration of fine particles and water from the subgrade, has been observed more often due to the increase of axle load and train speed. This paper presents a series of laboratory experiments to simulate mud pumping in rail embankments and provides a theoretical explanation. The test results show that the sloshing of slurries within a layered gravel-silt column under dynamic load causes the oscillation of excess pore pressure. The increase of turbidity will increase the sloshing damping of the slurry, thus causing the oscillation amplitude of excess pore pressure to decrease. A theory is proposed based on the dynamics of liquid sloshing, which confirms that the pressure gradient caused by slurry sloshing changes the seepage velocity in the subgrade soil, thereby providing the necessary hydrodynamic force for detachment and migration of fine particles. The relationship between the pressure gradient and loading frequency is acquired in numerical models and experiments. The engineering implications of this theoretical explanation are also discussed in the context of designing reasonable train speed.
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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) | 0.000 | 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) | 0.001 | 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".