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Record W3045951812 · doi:10.1139/cgj-2019-0650

Effects of electrokinetic phenomena on the load-bearing capacity of different steel and concrete piles: a small-scale experimental study

2020· article· en· W3045951812 on OpenAlexvenueno aff
Fatemeh Sadeghian, Abdolhosein Haddad, Soheil Jahandari, Haleh Rasekh, Togay Ozbakkaloglu

Bibliographic record

VenueCanadian Geotechnical Journal · 2020
Typearticle
Languageen
FieldEngineering
TopicElectrokinetic Soil Remediation Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsBearing capacityGeotechnical engineeringCementPileLimeCorrosionMaterials scienceElectrokinetic phenomenaBearing (navigation)Composite materialMetallurgyGeology

Abstract

fetched live from OpenAlex

To date, the electrokinetic (EK) method has only been used to increase the bearing capacity of steel piles. This study analysed the impact of EK on the bearing capacity of reinforced cement concrete piles (RCCP), reinforced lime-cement concrete piles (RLCCP), and steel piles located in kaolin clay. The performance of four different cathodes was also evaluated, and the iron electrode was found to be the most effective cathode for use in the EK process. Unlike RLCCP, the bearing capacity of 7 day cured RCCP with 5 day EK decreased due to corrosion in the pile body. However, the addition of lime to RCCP significantly increased the pile bearing capacity by 57.8% with 8 day EK and prevented damage and corrosion in the pile body. It is concluded that EK can effectively increase the bearing capacity of both metallic and even concrete piles.

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)0.000
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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)0.0010.000

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 head0.195
Teacher spread0.183 · 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

Citations38
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicElectrokinetic Soil Remediation TechniquesFrench-language works237,207