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Record W1974956842 · doi:10.1061/9780784412084.0040

Offshore Open End Steel Tubular Piles-A Case History

2012· article· en· W1974956842 on OpenAlexaff
L. S. Brzezinski, Hafeez U. Baba

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsSNC-Lavalin (Canada)
FundersKorea Resources Corporation
KeywordsPileTension (geology)Geotechnical engineeringSubmarine pipelineStructural engineeringCompression (physics)Bearing capacityDynamic testingGeologyEngineeringMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Steel piles of 1,219 and 1,016 mm diameter were driven open end in 16 to 20 m of water, to 36 to 44 m depth in marine soils of variable, but generally silty sand composition. The 308 piles support marine structures requiring maximum compression and tension service loads of 5,702 kN and 2,650 kN. The piles drove easily without soil plug development and driving resistances did not mirror the SPT profiles. Dynamic tests and CAPWAP analyses indicated soil set-up was essential to achieve pile capacities, but no clear trend emerged regarding required set-up duration. A pile subjected to static tension and dynamic compression tests indicated the static tension resistance was equivalent to 72 % of the dynamic shaft resistance and to K = 0.5. A static compression test on an unplugged pile indicated the average external/internal unit shaft resistance was 75 % of the unit tension resistance and about 50 % of the API predicted unit shaft resistance. External and internal friction was not equal and was grossly overestimated by the API method. Static and dynamic tests on another test pile indicated plugging had developed, as at this location internal shaft resistance was greater than toe end bearing.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.025
GPT teacher head0.212
Teacher spread0.187 · 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 designCase report
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

Citations3
Published2012
Admission routes1
Has abstractyes

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