Compressive and Tensile Strength of Nano-clay Stabilised Soil Subjected to Repeated Freeze–Thaw Cycles
Bibliographic record
Abstract
Abstract Improvement of the mechanical properties of clayey soils by additional elements to enhance the strength under numerous freezing and thawing cycles has been considered as a serious concern for engineering applications in cold regions. The objective of the current study is to investigate the effect of nano-clay as a stabiliser on the mechanical properties of clay. To this end, the clay specimens were prepared by adding various percentages of nano-clay ranging from 0.5% to 3% by dry weight of soil and were experimentally tested under the uniaxial compression and tensile splitting tests under different curing times (0, 7 and 28 days) after experiencing various freeze–thaw cycles ranging from 0 to 11. It can be concluded from the results that nano-clay particles may be used as a stabiliser in geotechnical applications to improve soil property. The results indicate that the optimum moisture content (OMC) of specimens increases and the maximum dry density (MDD) decreases with the increasing nano-clay content. The specimens containing about 1% nano-clay recorded maximum values of unconfined compressive strength (UCS) as well as tensile strength. For example, the addition 1% nano-clay increased the UCS and tensile values of clay specimens under the curing time of 28 days by 34% and 247%, respectively. In addition, the long-term durability of specimens against freeze–thaw cycles increases further with the addition of nano-clay content ranging from 2% to 3%.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".