Study on Crack Development and Micro-Pore Mechanism of Expansive Soil Improved by Coal Gangue under Drying–Wetting Cycles
Bibliographic record
Abstract
Expansive soil is prone to cracks under a drying-wetting cycle environment, which brings many disasters to road engineering. The main purpose of this study is use coal gangue powder to improve expansive soil, in order to reduce its cracks and further explore its micro-pore mechanism. The drying-wetting cycles test is carried out on the soil sample, and the crack parameters of the soil sample are obtained by Matlab and Image J software. The roughness and micro-pore characteristics of the soil samples are revealed by means of the Laser confocal 3D microscope and Mercury intrusion meter. The results show that coal gangue powder reduces the crack area ratio of expansive soil by 48.9%, and the crack initiation time is delayed by at least 60 min. Coal gangue powder can increase the internal roughness of expansive soil. The greater the roughness of the soil, the less cracks in the soil. After six drying-wetting cycles, the porosity and average pore diameter of the improved and expanded soil are reduced by 37% and 30%, respectively, as compared to the plain expansive soil. By analyzing the cumulative pore volume and cumulative pore density parameters of soil samples, it is found that the macro-cracks are caused by the continuous connection and fusion of micro-voids in soil. Coal gangue powder can significantly reduce the proportion of micro-voids, cumulative pore volume, and cumulative pore density in expansive soil, so as to reduce the macro-cracks.
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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 | 0.000 | 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".