A Finite Element Approach to Investigate the Deformation Behaviour in Deep Excavation for TBM Launching Shaft
Bibliographic record
Abstract
Being one of the densely populated cities in the world, Dhaka is going through massive changes for infrastructure construction.Various mega projects like underground metro have been undertaken by the government in recent years.This kinds of mega projects certainly need huge excavation works for underground stations, ventilation shaft, launching box and for many other reasons.A careful assessment of the excavation work is required to reduce the risk of failure during construction.Finite element analysis (FEM) can support as an excellent tool to understand the soil behaviour during excavation.As Dhaka has a layer of soft soil in the upper strata, the risks are also higher for these kinds of deep excavation works.This paper analyze a specific section in Dhaka city where future metro rail constructions can take place.An idealized section of a tunnel boring machine(TBM) launching shaft is considered for the excavation analysis where the concrete diaphragm wall has been considered as earth retaining system.Along with deformation, the forces have also been studied to understand the impact due to construction.
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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 | 0.000 |
| 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".