Mass Loss Measurement in Triaxial Permeameter Testing Review of Current Practices and Proposal for Advancement
Bibliographic record
Abstract
Triaxial permeameter testing is a useful method for studying the mechanical behaviour of internally eroded specimens and involves four stages: reconstitution, consolidation, seepage, and axial compression. Under downward seepage, flow is introduced to the top of the specimen, erodes it, and leaves the specimen carrying eroded particles through the featured base pedestal designed to accommodate unimpeded outward movement of eroded particles. Careful collection and precise measurement of any mass loss is crucial for accurate void ratio estimation and characterization of erosion response. An internally unstable specimen reconstituted against featured boundaries experiences mass loss not only within but also out of the seepage window. This article reviews current mass loss measurement practices during the seepage stage, identifies challenges and the corresponding need for mass loss measurement throughout a triaxial permeameter test, and proposes a comprehensive method for measuring mass loss from the start of reconstitution to the end of axial compression.
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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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".