Investigating the effect of temperature and water freezing on the response of geogrid composite
Bibliographic record
Abstract
Geosynthetics can be exposed to varying temperature and moisture conditions when embedded in soil, which can affect their mechanical properties. However, existing testing standards do not account for extreme environmental conditions such as low temperatures and ice formation. The aim of this study was to understand the effect of temperature variation and ice formation on the tensile properties of dry and wet geosynthetics by conducting single-rib tensile tests on a wicking geogrid composite in a temperature chamber. Tensile stress–strain curves were obtained at various temperatures for dry samples (−40°C to 40°C) and wet samples (0°C to −40°C). It was found that, with a decrease in temperature, the tensile strength and stiffness of dry and wet samples increased while the ultimate strain decreased. The freezing of water in wet samples also accelerated the rates of increase in ultimate strength and decrease in ultimate strain. The failure mode of the geogrid composite also changed with temperature, occurring at the middle junction at higher temperatures and closer to the end junctions with a fibrous appearance at lower temperatures. These findings provide insights into the significance of varying environmental conditions on geosynthetic properties.
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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".