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Record W2030780141 · doi:10.1680/grim.2008.161.3.131

Electrochemical stabilisation for offshore model caissons

2008· article· en· W2030780141 on OpenAlexaff
Eltayeb Mohamedelhassan, Julie Q. Shang, Mostafa A. Ismail, Mark Randolph

Bibliographic record

VenueProceedings of the Institution of Civil Engineers - Ground Improvement · 2008
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsWestern UniversityLakehead University
Fundersnot available
KeywordsCaissonCementation (geology)ElectrodeGeotechnical engineeringCalcareousMaterials scienceElectrochemistrySubmarine pipelineOffshore wind powerComposite materialGeologyEngineeringElectrical engineeringChemistryCement

Abstract

fetched live from OpenAlex

A laboratory-floor experimental study was conducted on the electrochemical treatment of calcareous sand for offshore foundations. A steel tube of diameter 200 mm and length 400 mm was used as a model caisson. Calcareous sand and seawater from the coastline of Western Australia were used in the study. Twelve electrodes made of perforated steel pipes, diameter 14 mm, length 450 mm and filled with soluble CaCl 2 granules as a cementing agent, were installed around the caisson. The electrochemical treatment tests were carried out with two electrode layout configurations in parallel with a control test. The electric power was applied via pairs of the steel pipe electrodes in the first configuration whereas the caisson served as one electrode in the second configuration. The applied direct current (d.c.) voltage was 8 V for the first configuration and 6 V for the second. The pullout resistance of the caisson after the treatment was increased by 140% to reach a value of 304%, in comparison with the control. The cementation generated by the treatment was demonstrated by the formation of a soil plug inside the caisson, soil cemented to the surface of the electrodes and caisson, and the significant increases in pullout resistances. The cementation effects were confirmed by electron microscopy images, X-ray fluorescence analyses and X-ray diffraction analyses.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.321
Threshold uncertainty score0.668

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.012
GPT teacher head0.192
Teacher spread0.180 · 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 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

Citations2
Published2008
Admission routes1
Has abstractyes

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