Theoretical and field investigation into the vacuum formation in the siphon-vacuum drainage system for soft ground improvement
Bibliographic record
Abstract
Compared to the traditional drainage consolidation measures for soft ground improvement, the siphon-vacuum drainage method (SVD) offers more advantages, for example, improved drainage efficiency, lower maintenance costs, lower demand for energy and materials, and less environmental impact. Hence, it is expected to be widely applied in soft ground improvement. However, the mechanism of vacuum formation in the system remains unclear. In this study, the vacuum formation mechanism of SVD is investigated based on the theoretical deduction of the variations of the water level and air pressures during the siphon drainage and seepage processes. A theoretical model is developed to describe the vacuum formation, allowing the estimation of the varying air pressure, water level, seepage rate, and discharge rate in the system. Moreover, a field investigation was carried out in Zhoushan, Zhejiang Province, to further validate the correctness of the developed model. This study also provides further insights and suggestions into the field application of SVD for soft ground improvement.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".