Pressuremeter Investigation for Mass Rapid Transit in Bangkok, Thailand
Bibliographic record
Abstract
The 20-km (12.5-mi) mass rapid transit underground railway system in central Bangkok, Thailand, recently opened for passengers. During construction, the project was divided into two separate civil design–build contracts: the northern section, comprising approximately 10 km (6.2 mi) of twin bored tunnels, and nine stations constructed within slurry walls by adopting top-down techniques. A crucial part of the design of the underground structures was the selection of appropriate design parameters for the slurry walls. The contractor was responsible for ground-related issues and carried out a detailed site investigation to confirm the ground conditions and define soil parameters for the design of the underground structures. The site investigation comprised 40 conventional wash-bored borings and six self-boring pressuremeter tests. This paper describes the site investigation that was carried out for the project and the ground conditions that were encountered, with particular focus on the use of the self-boring pressuremeter to estimate the soil strength, stiffness, and in situ pressure for use in design of the slurry walls. The paper discusses the various methods used to interpret the data and compares the parameters derived from the pressuremeter to those derived from other methods and from back-analysis of the behavior of the wall during construction. It is concluded that in the conditions in Bangkok, the pressuremeter testing provided higher strength and stiffness values than determined from other methods and that these parameters were subsequently borne out by the behavior of the underground structures.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".