Effect of zeolite utilization on volume change and strength properties of expansive soil as landfill barrier
Bibliographic record
Abstract
A sand–Na–bentonite mixture is widely used as engineering barrier material, which usually possesses hydraulic conductivity below the regulatory limit (10−7 cm/s). However, in some areas natural Na–bentonite is not readily available; instead, an abundantly prevailing local expansive soil can be an alternative. This study assesses the suitability of a local expansive soil mixed with zeolite, easily obtained from natural reserves in Turkey, proposed to be used as a landfill liner in a semi-arid climate. The choice of zeolite is due to its already well-understood high adsorption capacity for heavy metals as well as its pozzolanicity. The volume change, strength, and hydraulic conductivity characteristics were studied with respect to durability through ageing. When an expansive soil to zeolite ratio of 0.5 was used, the results indicated improved properties with curing. Swell potential was observed to decrease by 85% within a 90 day curing period, while a 30%–34% reduction was noted in shrinkage and compressibility characteristics. The hydraulic conductivity was observed to remain below the regulatory limit under all confining pressure ranges studied, provided the curing time was at least 90 days. Moreover, the mixture attained improved strength characteristics with time, and proved to be sustainable over the period studied. Therefore, it was concluded that expansive soil mixed with zeolite could be a good alternative to sand–Na-bentonite, mainly in developing areas of growing population and environmental degradation.
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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".