Filtration behaviour of staple fibre geotextiles under unequal biaxial tensile strains
Bibliographic record
Abstract
Gradient ratio tests were conducted to investigate the filtration behaviour of staple fibre needle-punched nonwoven geotextiles subjected to unequal biaxial tensile strains. Three groups of biaxial tensile strains were designed, with the ratios of the strain in the machine direction to that in the cross-machine direction set to 1, 2, and 4, respectively. The strains in the machine direction in the three groups were the same, ranging from 10% to 30%. The tested filtration properties included the gradient ratio (GR), permeability of the soil-geotextile system, mass of soil loss, and permittivity of the pure geotextiles. Comparisons were made between the filtration properties of staple fibre (SN) geotextiles and continuous filament (CN) geotextiles. It is shown that for a certain strain ratio, the GR value at the time of test termination increases with increasing strain, and the permeability of the soil-geotextile system, soil loss, and permittivity of the pure geotextiles decrease with increasing strain. The soil loss and permittivity under equal biaxial tensile strains tend to be higher than those under unequal biaxial tensile strains. The CN geotextiles have better retention capability and more clogging potential for the tested soils than the SN geotextiles for a similar mass per unit area.
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 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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".