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Record W3092316681 · doi:10.1139/cgj-2020-0084

Experimental study of an innovative driven and grouted soil nail (x-Nail)

2020· article· en· W3092316681 on OpenAlexvenueno aff
Mohammad Zahidul I. Bhuiyan, Shanyong Wang, John Carter

Bibliographic record

VenueCanadian Geotechnical Journal · 2020
Typearticle
Languageen
FieldEngineering
TopicGrouting, Rheology, and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsGroutSoil nailingNail (fastener)Geotechnical engineeringCompactionGeologyMaterials scienceEngineeringStructural engineering

Abstract

fetched live from OpenAlex

This paper describes an experimental investigation of a newly developed driven and grouted soil nail (x-Nail), which combines the capabilities of a purely frictional driven nail and a compaction-grouted nail. The innovative design allows the x-Nail to be driven into the ground with a latex balloon attached that is subsequently used for compaction grouting. A grout bulb is thus formed at the driven end of the nail to improve its pull-out resistance. For compaction grouting, a special type of additive−mixed cement grout was used in this investigation because of its zero bleeding and high bond strength. A series of pullout model tests was conducted to examine the performance of the x-Nail compared to a purely frictional soil nail. It was found that more than 90% of the pullout force of the x-Nail was resisted by the expanded grout bulb and the end bearing resistance of the grout bulb increased with the increment of the injected grout volumes. The experimental results revealed that the pullout force of the x-Nail increased approximately 1800%, 1550%, 1200%, and 900% compared to the purely frictional soil nail for the injected grout volumes of about 350, 270, 220, and 170 mL, respectively.

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)0.001
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.017
GPT teacher head0.224
Teacher spread0.207 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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Same venueCanadian Geotechnical JournalSame topicGrouting, Rheology, and Soil MechanicsFrench-language works237,207