Effects of sodium chloride crystallization on shear characteristics of road base aggregates under unsaturated state
Bibliographic record
Abstract
The precipitation and intrusion of sodium chloride into pavement structures is inevitable in coastal regions, which can affect the mechanical properties of the road base courses. To investigate this problem, samples with sodium chloride solution were cured in a thermostatic chamber until they reached the specified states of sodium chloride precipitation within the pores. A critical crystallization degree ( ωc) was discovered by computerized tomography scan, corresponding to the start of the formation of porous salt crust cementing the soil particles. A series of unsaturated large-scale triaxial shear tests were then conducted under various states of salt crystallization. The results showed that in the early stages of crystallization (i.e., ω < ωc), the peak stress and internal friction angle decreased with ω because of the coating and lubricating effects of salt powders, while the apparent cohesion remained constant. When ω > ωc, owing to the increasing adsorption and cementation effects of the salt crust, rapid growth was observed for the peak stress, internal friction angle, and apparent cohesion of the road base aggregates. Considering the influence of salt precipitation, a modified shear strength criterion that can predict the shear strength of the salinized road base aggregates was formulated.
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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".