Stabilization of Sandy Soils by Bentonite Clay Slurry at Laboratory Bench and Pilot Scales
Bibliographic record
Abstract
Sand is one of the most abundant, naturally occurring materials in many parts of the world, which is used in local rural areas in infrastructure projects such as in the construction of low volume paved and unpaved road layers due to their availability at low cost and scarcity of other suitable construction materials. Several geotechnical solutions for sand stabilization have been undertaken to improve their properties in order to overcome erosion, failure of pavements under traffic loading, embankments, cuts and excavations caused by failures of sand structure. In this investigation, bentonite clay–water slurry was used due to its cohesive and eco-friendly nature to improve sand strength by the means of manual injection in the laboratory and pilot scales. Sand was stabilized using variation of bentonite clay contents, 0%, 1%, 2%, 3%, and 4% (by weight of dry sand), at different curing times: 0 days, 1 day, 2 days, and 3 days. Direct shear tests were conducted to determine shear strength parameters for sand before and after stabilization process. Furthermore, a transparent polypropylene box (60 cm × 40 cm × 30 cm) was used in this study as a larger scale for sand stabilization technique by applying manual grouting of bentonite clay–water slurry to the sand mass. A mechanical shaker was used at 100, 200, 300, and 400 rpm for 10 min at each stage to test the stability of sand in addition to using a Scanning Electron Microscope (SEM) to obtain images for stabilized sand and Ground Penetrating Radar (GPR) to scan soil mass before and after stabilization. The test results showed that a slurry composed of 3% of bentonite clay additive with 10.3% added water by weight of dry sand mass are the optimum amounts for the stabilization process, which provides a substantial resistance to shear forces.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".