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Record W3171328849 · doi:10.1139/cgj-2020-0078

Field axial loading tests of screw micropiles in sand

2021· article· en· W3171328849 on OpenAlexaffvenue
Mujtaba Khidri, Lijun Deng

Bibliographic record

VenueCanadian Geotechnical Journal · 2021
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGeotechnical engineeringTorquePileStrain gaugeStructural engineeringEngineeringPenetration testCone penetration testLateral earth pressureGeology

Abstract

fetched live from OpenAlex

A screw micropile consists of a smooth shaft at the top, threaded shaft at the middle, and tapered shaft at the bottom. Research is required to investigate the axial behavior and capacities of this pile type in sand. A field load test program was performed on six types of full-scale screw micropiles installed at a sandpit site using torque. Selected piles were instrumented with axial strain gauges. A geotechnical investigation, including cone penetration tests (CPTs) and standard penetration tests, was undertaken. In total, 41 piles, including eight instrumented piles, were tested. The ultimate capacities and the unit shaft resistance distributions were determined. The shaft resistance was then compared with the tip resistance of CPT. The coefficient of lateral earth pressure and combined shaft resistance factor was determined for each pile segment, and then an effective stress method based on the combined shaft resistance factor was used to estimate the capacity of test piles. A theoretical torque model was developed using CPT sleeve friction; the model was verified by comparing the estimated torque to the measured torque of test piles. In the end, empirical torque factors were developed.

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 score0.004
Threshold uncertainty score0.009

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.008
GPT teacher head0.196
Teacher spread0.188 · 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

Citations14
Published2021
Admission routes2
Has abstractyes

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