An evaluation of base soil-filter compatibility using a triaxial permeameter
Bibliographic record
Abstract
Filtration compatibility of base soil and granular filter materials must be addressed in the design of zoned engineered fill structures. The evolution of design practice governing filter compatibility is reviewed, with emphasis placed on the experimental studies that have made the greatest contribution to current guidelines. Design practice governing filter compatibility for cohesionless uniform materials has remained relatively unchanged for the last 70 years. A novel and improved triaxial permeameter is used to test base soil-filter grain size ratios (D₁₅/d₈₅) close to the limit of filter incompatibility. The configuration and operation of the test device are described. Thereafter, data are reported for select combinations of base soil-filter specimens of glass beads that are reconstituted, consolidated and subject to unidirectional seepage flow. Interpretation of the test results addresses the onset of filter incompatibility with reference to independent measurements of change in permeability of the two-layer system and mass loss of the base soil through the filter. A unified framework is presented for interpretation of filter incompatibility, taking into account the influence of stress and hydraulic gradient. The implications of the test results are analyzed and discussed with reference to a confident understanding of base-soil filter compatibility.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".