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Record W2022935860 · doi:10.1139/t06-021

Physical modelling of consolidation of Hong Kong marine clay with prefabricated vertical drains

2006· article· en· W2022935860 on OpenAlexvenueno aff
Zhen Fang, Jian‐Hua Yin

Bibliographic record

VenueCanadian Geotechnical Journal · 2006
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
FundersHong Kong Polytechnic UniversityGovernment of Jiangxi Province
KeywordsConsolidation (business)Pore water pressureGeotechnical engineeringPermeability (electromagnetism)ResidualGeologyMaterials scienceComposite materialChemistry

Abstract

fetched live from OpenAlex

In this study, a small-scale physical model with full instrumentation was set up and used to measure the full consolidation process of a cylinder of clay with one prefabricated vertical drain (PVD) in its middle. The model test produced several interesting phenomena: (i) a delayed pore-water pressure increase under a constant pressure during loading stages, (ii) a delayed pore-water pressure decrease under a constant pressure during unloading stages, and (iii) residual excess pore-water pressures at the end of loading. Two analytical solutions accounting for the well resistance and a smear zone with reduced permeability are used to calculate the variation of average excess pore-water pressure with time, and these are compared with the measured variation. The well resistance of the PVD has a larger influence on the consolidation process than the permeability of the smear zone, especially during the latter stages of consolidation. The analytical solutions are able to show the influence of the well resistance of the PVD strip, but they cannot satisfactorily simulate the pattern of the residual excess pore-water pressure with time.Key words: consolidation, vertical drain, marine clay, physical modelling.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.337
Threshold uncertainty score0.698

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 integrity0.0000.001
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 head0.175
Teacher spread0.167 · 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

Citations31
Published2006
Admission routes1
Has abstractyes

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