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Record W2011487215 · doi:10.1061/9780784412350.0067

Fracture Deformation Measurements during Grouting in Hard Rock

2012· article· en· W2011487215 on OpenAlexaff
Johan Thörn, Edward Runslätt, Åsa Fransson, Johan Funehag, Gunnar Gustafson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGrouting, Rheology, and Soil Mechanics
Canadian institutionsGolder Associates (Canada)
Fundersnot available
KeywordsGeotechnical engineeringBoreholeStiffnessDeformation (meteorology)GeologyRock mass classificationFracture (geology)Stress (linguistics)Structural engineeringEngineering

Abstract

fetched live from OpenAlex

When a fracture system in crystalline rock is grouted the rock mass may deform. Such deformations may reduce the grouting efficiency since new flow paths are opened. The work presented here shows that deformations occur at hydraulic tests and grouting and that deformation can be measured and evaluated as stiffness from in situ tests. Deformation measurements, hydraulic testing, and grouting was conducted in spring 2010 in the Hallandsås tunnel and hydraulic testing in a service tunnel in Gothenburg (Runslätt and Thörn, 2010). For measuring physical deformation recently developed equipment from Chalmers University of Technology was used. Deformations were measured seven times in the same borehole. Three measurements were during grouting, and the remaining four from water pressure tests. Most deformations occurred at pump pressures of 1-1.4 MPa, which is lower than the calculated normal rock stress. Stiffness has been evaluated in several ways, including a new method, (Fransson, et al., 2010). Generally the evaluated stiffness is lower in the Hallandsås tunnel than in the Gothenburg tunnel. The results show agreement with other in situ experiments.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.022
GPT teacher head0.211
Teacher spread0.189 · 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 designBench or experimental
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

Citations1
Published2012
Admission routes1
Has abstractyes

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