Drainage performance of wicking geotextiles under rainfall and capillary rise conditions
Bibliographic record
Abstract
Wicking geotextiles have been developed to overcome the limitations of conventional geotextiles in unsaturated soil conditions. Over the past decade, research has demonstrated the effectiveness of woven wicking geotextiles in draining capillary water and improving lateral drainage. However, the performance of nonwoven wicking geotextiles under different drainage conditions remains largely unexplored. This study assesses the effectiveness of nonwoven wicking geotextiles in various unsaturated soils using soil column and soil box tests to simulate capillary rise and rainfall, respectively. In the column test, clayey sand was used to evaluate capillary rise, while the box test examined two subgrade materials: Ottawa sand (well-draining) and clayey sand (poorly draining). Volumetric water content was monitored under three conditions: wicking geotextile, non-wicking geotextile, and a control with no geotextile. Results indicate that the wicking geotextile significantly restricts capillary rise, reducing it by around 100 mm in clayey sand columns. After rainfall, wicking geotextile prevents water accumulation above the geotextile and enhances drainage efficiency in both sand types, with superior performance in Ottawa sand. By limiting upward water movement and promoting effective drainage, the wicking geotextile mitigates moisture-induced instability risks in embankments, offering substantial advantages over conventional geotextiles for geotechnical drainage applications.
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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".