MétaCan
Menu
Back to cohort
Record W1518502626 · doi:10.1177/0361198105192800122

Pressuremeter Investigation for Mass Rapid Transit in Bangkok, Thailand

2005· article· en· W1518502626 on OpenAlexaff
Richard E. Prust, J D Davies, Shuang Hu

Bibliographic record

VenueTransportation Research Record Journal of the Transportation Research Board · 2005
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsArup Group (Canada)
Fundersnot available
KeywordsStiffnessGeotechnical engineeringEngineeringSlurryCivil engineeringLateral earth pressureStructural engineering

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.861
Threshold uncertainty score0.746

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.059
GPT teacher head0.314
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueTransportation Research Record Journal of the Transportation Research BoardSame topicGeotechnical Engineering and Underground StructuresFrench-language works237,207