Cement-Improved Wetting Resistance of Coarse Saline Soils in Northwest China
Bibliographic record
Abstract
Abstract Wetting-induced collapse of coarse saline soil foundations is a frequently encountered problem in the inland basin of Northwest China, but this particular behavior and relevant treatment have not been given adequate attention. Specimens treated by silicate cement were used in wetting collapse testing at conventional foundation loads, with five cement contents and four curing durations considered. The results indicate that in the case of no curing, the collapsible deformation during wetting declines at higher cement contents, and a stepwise development of deformation was noticed over the wetting duration. Specimens treated by cement after curing exhibit a decrease in the compressive deformation during wetting, and part of them show volume expansion instead. The complex hydrolysis and hydration reaction of cement in the process of curing primarily accounts for this. Moreover, the collapsibility coefficient varies within a narrow range in the noncuring case, proving the limited influence of cement inclusion; however, a gentle range, from 2.0 to 4.0 %, can be found after curing, beyond which it slightly varies. An elastoplastic model was established, incorporating a variable boundary seepage equation, and was then used for modeling a field immersion test. The rationality of the model was verified by comparing the measured and simulated results, including the degree of saturation and vertical displacement. The optimal depth and width for cement treatment was discussed in view of the practical engineering.
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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) | 0.000 | 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 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".