How to protect adjacent bridges due to tunnel excavation: a case study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper presents a systematic approach with detailed step-by-step procedures for assessing safety risk of existing bridges in tunnel construction. The potential safety risk of a specific adjacent bridge is assessed within four different risk levels, with the spatial neighbor relation (hazard component) and the bridge health condition (vulnerability component) taken into account. Corresponding preventive measures for bridges at different risk levels are further provided according to risk assessment results. A reasonable balance between the project system safety and budget constraints is reached, where the assessed risk level plays a decisive role in the adoption of numerous simulation analysis tools. The proposed approach is applied in the construction of Wuhan Metro Line 2 (WML2) as a case study. The impact of the foundation excavation on adjacent bridge piers is further analyzed. Results demonstrate the feasibility of the developed approach, as well as its application potential.
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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 | 0.000 | 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 it