Air–Water Flows in a Deep Tunnel Downstream of a Dropshaft
Bibliographic record
Abstract
Dropshafts of deep tunnel systems can entrain a large amount of air, and the resulting air–water interactions cause potential safety issues. In this study, the air–water flow characteristics along a tunnel under the effect of air entrainment of an upstream dropshaft and air release from a downstream airshaft were investigated experimentally with a large-sized physical model. Various regimes of air–water flow along the tunnel under different conditions of water inflow rates and downstream water levels were observed. The pressure fluctuations along the tunnel exhibited periodic features in amplitude, which were analyzed with variational mode decomposition and the Hilbert transform. The cause of pressure fluctuations in the tunnel was then explored. The results showed two major peaks of the pressure data corresponding to the frequencies of 0.2 and 1.8 Hz. The pressure component of 0.2 Hz was caused by the slug frequency of the air–water flow, and the other was related to the periodic air release from downstream in the form of air pockets. The findings of this study can contribute to a better understanding of the air–water flow features in deep tunnel systems.
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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 | 0.001 | 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) | 0.000 | 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".