Fracture morphology of desiccation cracks in clayey soil
Bibliographic record
Abstract
Desiccation cracks compromise soil integrity and weaken its strength, causing a range of detrimental consequences across various domains. Elucidating the cracking mechanism can aid in managing crack propagation and mitigating the associated risks. This study monitored and compared the evolution of crack patterns on the soil surface and fracture morphologies on the soil cross-section during the drying process using a tested soil sample. Multiple fracture morphological features are discerned on the soil cross-section, encompassing initiation points and plumose structures. Soil fracture morphologies are categorized into three cases based on the initiation point's location, referred to as “Top-initiated structure”, “Bottom-initiated structure”, and “Truncated structure”. Experimental results demonstrate that plumose structures result from the division of the crack front under mixed-mode loading. Cracking under mixed-mode I + II loading leads to cross-section tilting, resulting in curved surface cracks. Conversely, cracking under mixed-mode I + III loading causes cross-section twisting, generating hackle lines and step structures. Furthermore, the crack front radiates from the initiation point, creating orthogonal hackle lines. The geometric relationship confirms that the soil fracture morphology is a good indicator of the cracking process, both in laboratory tests and field observations.
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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 | 0.001 | 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".