Inception of geohydraulic failures in granular soils – an experimental and theoretical treatment
Bibliographic record
Abstract
This paper outlines an experimental investigation into seepage-induced failures in soils subjected to static and cyclic loading. Internally stable, marginal and unstable soils are characterised by heave, composite heave–piping and suffusion that develops immediately upon instability. In this study, the stable specimens exhibited heave at larger hydraulic gradients than the unstable specimens failing by suffusion at relatively smaller hydraulic gradients. Under no external load (i.e. self-weight only), the relative density (Rd) and particle size distribution (PSD) in tandem controlled the internal stability of soils, although the effective stress magnitude (σ′vt) also had a role to play under both static and cyclic loading conditions. Instability in soils was governed by specific combinations of their geo-hydro-mechanical characteristics such as PSD, Rd, stress reduction factor, critical hydraulic gradients and associated effective stress levels. These factors are combined to model the development and inception of instability, and the paper offers visual guides as a practical tool for practitioners. Each soil has a unique critical envelope related to its PSD and Rd, and a critical path with its inclination that depends on the hydro-mechanical conditions. The current results of internal erosion tests conducted by the authors plus those adopted from published literature are used to verify the proposed model.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".