Stabilization of a highly expansive soil using waste-tire-derived aggregates and lime treatment
Bibliographic record
Abstract
This study investigates the combined efficacy of waste-tire-derived aggregate (TDA) materials and hydrated lime on the compactability, compressive strength and swelling potential of a highly expansive soil from South Australia. A total of 21 mix-designs, covering a comprehensive range of soil–TDA–lime combinations, were examined through standard Proctor compaction, unconfined compressive strength (UCS) and oedometer swell tests. The mobilized UCS exhibited a ‘rise–fall’ behavior, peaking at 5% TDA content and subsequently decreasing (monotonically) for higher inclusions of TDA. Increasing the TDA mean particle size (from 1.67 to 3.34 mm) also contributed positively to the UCS development. Addition of TDA to the soil/soil–lime-blends produced notable reductions in the swelling potential; the reduction was primarily governed by higher TDA contents, and, to a lesser degree, for larger TDA mean particle sizes. However, the role of TDA particle size in reducing swelling was found to be more significant than that of enhancing the UCS. As expected, lime treatment of the soil–TDA blends provided major further improvements to the UCS and swelling potential reduction; the achieved UCS improvements being positively proportional to the lime content and curing time. In view of the experimental results, soil–lime blends containing TDA to soil–lime mass ratios of up to 10% (preferably employing coarse-sand-sized equivalent TDA) can be deemed as suitable choices (capable of adequately mitigating the swelling potential, while simultaneously enhancing the UCS).
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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".