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Record W2071123005 · doi:10.1520/gtj11046j

An Electrokinetic Testing Apparatus for Undisturbed/Remoulded Soils under In-Situ Stress Conditions

2000· article· en· W2071123005 on OpenAlexaff
JQ Shang, KL Masterson

Bibliographic record

VenueGeotechnical Testing Journal · 2000
Typearticle
Languageen
FieldEngineering
TopicElectrokinetic Soil Remediation Techniques
Canadian institutionsWestern University
Fundersnot available
KeywordsElectrokinetic phenomenaGeotechnical engineeringPore water pressureStress (linguistics)GeologySoil testMaterials scienceSoil waterCementation (geology)Composite materialSoil science

Abstract

fetched live from OpenAlex

Abstract In this paper, the design and construction of an apparatus for the study of electrokinetics are presented in detail. The apparatus is capable of both applying a designated effective stress to a soil sample and measuring the volume change and pore pressure during the electrokinetic testing. The results of a high voltage electrokinetic test on a remolded natural clay sample are reported to illustrate the operation of the apparatus and to study the mechanism of high voltage electrokinetics. During the 91 day test period of, including the application of a high voltage (−10 kV to −12 kV) for 51 days via insulated electrodes, the volume and pore pressure changes were negligible. Nevertheless, the geotechnical properties of the soil significantly improved, including increases in shear strength (69%), shear modulus (151%) and preconsolidation pressure (700%). Since the increases are calculated with respect to the control sample under identical effective stress and drainage conditions over the same time period, they can only be attributed to high voltage electrokinetic effects, possibly cementation bonding, diagenesis, and ionic diffusion. The electrokinetic testing apparatus developed in this study provides a viable tool for the study of electrokinetics on clayey soils for better understanding of the mechanisms involved in the process.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.204
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.025
GPT teacher head0.284
Teacher spread0.259 · 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.

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

Citations8
Published2000
Admission routes1
Has abstractyes

Explore more

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