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Record W2135081432 · doi:10.1139/t00-024

Modélisation numérique des mouvements de terrain meuble induits par un tunnelier

2000· article· en· W2135081432 on OpenAlexvenueno aff
Sadok Benmebarek, Richard Kastner

Bibliographic record

VenueCanadian Geotechnical Journal · 2000
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)ShieldSettlement (finance)Geotechnical engineeringGeologyTerrainComputer simulationNumerical modelingComputer scienceSimulationGeography

Abstract

fetched live from OpenAlex

The construction of shallow tunnels causes movements that can affect existing structures, inducing unacceptable disorders. These disorders can not only result from settlements but also from horizontal displacements. In the case of tunneling with pressurized face shield boring machines, ground movements are found to be the result of complex interactions between soil, construction stages, and shield drive parameters. In this context, the direct prediction of final ground movements by empirical, or analytical, and numerical approaches has proven to be insufficient. It is therefore necessary to develop and to validate more accurate simulation tools to allow assessment of the magnitude and distribution of soil movements in relation to construction stages. By experimental results of two sections of the Lyons D line subway extension (1993-1995), the authors examine various numerical procedures, in this paper. A two-dimensional procedure, taking into consideration various stages of construction, is proposed. The confrontation of this approach to experimental results shows the necessity of corrections due to three-dimensional effects of various tunneling stages.Key words: tunnels, shield, settlement, monitoring, grout, numerical modeling, back-analysis.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.308
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.190
Teacher spread0.183 · 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.

Study designSimulation or modeling
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

Citations10
Published2000
Admission routes1
Has abstractyes

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