MétaCan
Menu
Back to cohort
Record W2070301546 · doi:10.1139/t01-060

The effect of air flow on the shear strength of soil in compressed-air tunneling

2001· article· en· W2070301546 on OpenAlexvenueno aff
Akbar A. Javadi, C Snee

Bibliographic record

VenueCanadian Geotechnical Journal · 2001
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsGeotechnical engineeringShear (geology)Quantum tunnellingShear strength (soil)Compressed airCompressive strengthSoil waterAirflowMechanicsGeologyEngineeringMaterials scienceSoil scienceComposite materialPhysicsMechanical engineering

Abstract

fetched live from OpenAlex

This paper presents a method for studying the variation in shear strength of soil due to the air flow in compressed-air tunneling. The method is based on application of the shear strength theories of unsaturated soils in conjunction with a finite element model, developed by the authors, for analyzing the flow of the air through soils. The formulation of the problem, the numerical model, the design and modification of the triaxial cell and the laboratory testing program, and the results are presented and studied with particular reference to compressed-air tunneling. The results are presented and interpreted using the concepts and theory of shear strength for unsaturated soils. The results of the tests indicate the way in which the air pressure increases the stability of the ground, besides being an internal support, prior to the installation of the temporary or permanent lining. From the results of the tests, a three-dimensional failure envelope was plotted that can be used to predict the change in shear strength of the soil due to a change in the air pressure, in compressed-air tunneling. This information can be used to assess the risk of tunnel collapse and blow out. It also improves the current understanding of the interaction between the compressed-air tunneling method and the ground.Key words: compressed-air tunneling, air flow, unsaturated soils, shear strength.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.468

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.005
GPT teacher head0.183
Teacher spread0.179 · 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 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

Citations5
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicGeotechnical Engineering and AnalysisFrench-language works237,207