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Record W2137788482 · doi:10.1139/cgj-2013-0473

Capacity of dynamically embedded plate anchors as assessed through field tests

2014· article· en· W2137788482 on OpenAlexvenueno aff
A. Blake, Conleth O’Loughlin, Christophe Gaudin

Bibliographic record

VenueCanadian Geotechnical Journal · 2014
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
Fundersnot available
KeywordsEmbedmentCentrifugeBearing capacityGeotechnical engineeringStructural engineeringSeabedOffshore geotechnical engineeringBearing (navigation)EngineeringGeologyPhysics

Abstract

fetched live from OpenAlex

A dynamically embedded plate anchor (DEPLA) is a rocket-shaped anchor that penetrates to a target depth in the seabed by the kinetic energy obtained through free-fall and by the anchor’s self-weight. After embedment, the central shaft is retrieved leaving the anchor flukes vertically embedded in the seabed. The flukes constitute the load bearing element as a plate anchor. This paper presents and considers field data on the embedment depth loss due to the plate anchor keying process and the subsequent bearing capacity factor of the plate anchor element. The loss in plate anchor embedment was significantly higher than that reported from corresponding centrifuge tests and is reflected in the larger padeye displacements required to mobilize peak capacity in the field tests. Measured plate capacities and plate rotations during keying indicate that the end of keying coincides with the peak anchor capacity. Experimental bearing capacity factors are in the range N c = 14.3–14.6, which is appreciably higher than existing solutions for vanishingly thin circular plates. The higher N c for the DEPLA is considered to be due to a combination of the cruciform fluke arrangement and the fluke (or plate) thickness.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.450
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.008
GPT teacher head0.209
Teacher spread0.202 · 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

Citations29
Published2014
Admission routes1
Has abstractyes

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