Investigating Surface Settlements During Shield Tunneling Using Numerical Analysis
Bibliographic record
Abstract
The development of the subway system in Shenyang City, China, plays a vital role in alleviating traffic congestion and promoting sustainable societal growth. However, the deformation of the surface caused by the tunneling of the shield presents a significant threat to the structural integrity of Shenyang Subway Line 2 and adjacent geotechnical structures. To tackle this challenge, a set of FEA (finite element analysis) simulations were carried out to examine surface deformation under various construction scenarios for Line 2. These simulations were compared with empirical formulas and numerical analyses conducted using Midas GTS NX 2019 software, in addition to actual site measurements. The outcomes of the finite element analysis (FEA) demonstrated a closer alignment with the empirical data than with traditional formulas. The maximum deformation was observed to be approximately twice as large as the equivalent diameter at the back of the excavation face. The analysis indicated that surface deformation is inversely correlated with overburden thickness (H), soil elasticity (E), and the grout filling rate of the shield tail (ψ), while it is directly proportional to the shield’s outer diameter (D). This study provides important methods used in the shield tunneling process employed in the Shenyang subway and suggests that the developed methodologies may be applicable to similar subway projects.
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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 | 0.000 | 0.002 |
| 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".