Swell–Shrink Behavior of Rubberized Expansive Clays during Alternate Wetting and Drying
Bibliographic record
Abstract
The present study examines rubber’s capacity of improving the swell–shrink potential of expansive clays. Two rubber types of fine and coarse categories with different geometrical features were considered. The test program consisted of standard Proctor compaction and cyclic wetting–drying tests. Scanning electron microscopy (SEM) analysis was also performed to identify the soil–rubber amending mechanisms, and to observe the evolution of fabric in response to alternate wetting and drying. Cyclic wetting–drying led to the reconstruction of the soil/soil–rubber microstructure by way of inducing aggregation and cementation of the soil grains. The greater the number of applied cycles, the lower the swell–shrink features, following a monotonically decreasing trend, with the rubberized blends holding a notable advantage over the virgin soil. The tendency for reduction, however, was in favor of a larger rubber size, and more importantly the rubber’s elongated form factor; thus, predicating a rubber size/shape-dependent amending mechanism. The soil–rubber amending mechanisms were discussed in three aspects—increase in non-expansive content, frictional resistance generated as a result of soil–rubber contact, and mechanical interlocking of rubber particles and soil grains. The swell–shrink patterns/paths indicated an expansive accumulated deformation for the virgin soil, whereas the rubberized blends manifested a relatively neutral deformational state, thereby corroborating the rubber’s capacity to counteract the heave and/or settlement incurred by alternate wetting and drying.
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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".