New index to identify karst caves based on operational parameters during shield tunnelling
Bibliographic record
Abstract
Real-time karst cave identification is crucial to ensuring safety during shield tunnelling. However, owing to a sparsity of drilling data, karst caves often remain undetected before shield tunnelling begins. An approach is proposed for identifying karst caves in real time during shield operations. A new index, called the karst cave identification index (KCII), is proposed based on a force equilibrium analysis on the excavation face of a shield. The force balance conditions necessary to maintain the stability of the excavation face are derived according to soil pressure balance principles. Operational parameters related to the pressure balance process are then used to calculate the KCII, which leverages the operational parameters recorded by the sensory system of the shield machine. The effectiveness of the KCII was validated through a field case of shield tunnelling in Xuzhou, China, and it was compared with four other indices: specific energy, face penetration index, torque penetration index, and geological feather identification index. The comparison shows the difficulty of identifying karst caves using the other indices, but the KCII can be used to distinguish geological types and differentiate various types of karst cave filling. The KCII enables engineers to identify types of karst cave in real time, thus making necessary adjustments to shield operations possible and enhancing safety and efficiency in tunnelling.
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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 | 0.001 |
| 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".