Geocomposite capillary barriers to reduce frost heave in soils
Bibliographic record
Abstract
We investigated the potential for geosynthetic capillary barriers to reduce frost heave in soils by freezing upright, cylindrical soil specimens with horizontal disks of geosynthetics placed in them. During freezing, water was freely available at 25 mm above the base of 150 mm high specimens. The geosynthetics were located 5 mm above the water supply. We measured frost heave and final water content profiles of specimens containing geosynthetic capillary barriers and control specimens. The thermal conditions of the tests were typical of pavements in cold regions. Geotextiles prepared to simulate field conditions (i.e., moistened and containing soil fines) failed to significantly reduce frost heave. However, geocomposites comprising needle-punched polypropylene geotextiles sandwiching a drainage net, prepared in the same way as the moistened geotextiles containing soil fines, reduced frost heave when the soil water suction head in the overlying soil was 1800 mm or more. The geocomposites did not significantly reduce heave when the soil water suction head in the overlying soil was 800 mm or less. This is probably due to water migration between the two layers of soil, through the geotextiles and along the net of the geocomposite.Key words: capillary barrier, frost heave, geosynthetic, geotextile, geocomposite, soil freezing.
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 | 0.000 |
| 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".