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Record W4391250242 · doi:10.1139/cgj-2023-0439

Shadowing effect of an existing tunnel on the evolution of soil arching: impact of tunnel shape

2024· article· en· W4391250242 on OpenAlexvenueno aff
Ruixiao Zhang, Dong Su, Xing‐Tao Lin, Hong-Jun Lou, Xiangsheng Chen

Bibliographic record

VenueCanadian Geotechnical Journal · 2024
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
FundersShenzhen UniversityNational Natural Science Foundation of China
KeywordsGeotechnical engineeringGeologyEngineeringForensic engineering

Abstract

fetched live from OpenAlex

This study evaluates the shadowing effect of existing tunnels on the evolution of soil arching, focusing on the shape of the tunnel (circular and rectangular) through trapdoor experiments. The displacement and shear strain distributions of ground soil resulting from trapdoor movement were estimated using a digital image correlation technique. The results showed that the shadowing effect of the rectangular tunnel was significantly greater than that of the circular tunnel of the same size. The sand above the tunnel was displaced in a double-groove pattern owing to the presence of the tunnel, and the maximum surface settlement occurred between the tunnel boundary and the trapdoor edge. The circular tunnels exhibited consistently higher maximum surface displacements than that in the rectangular tunnels. The shear strain value of soil was lower for the rectangular tunnel case than that for the circular tunnel case. The rectangular tunnels required lesser trapdoor displacement than that of the circular tunnel to obtain the minimum soil arching ratio. The minimum and ultimate soil arching ratios increased as the burial depth ratio increased for both the tunnel shapes. The maximum stress ratio of the tunnel crown was consistently larger for the circular case than for the rectangular case.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.235
Teacher spread0.225 · 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 source (direct Gemma or distilled Codex), 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

Citations10
Published2024
Admission routes1
Has abstractyes

Explore more

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