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Record W4294091442 · doi:10.1139/cgj-2022-0083

Consolidation theory of slurry dewatered by permeable geotextile tube with distributed prefabricated drains

2022· article· en· W4294091442 on OpenAlexvenueno aff
Hao Zhang, Xueyu Geng, Honglei Sun, Yongfeng Deng, Sijie Liu, Yuanqiang Cai

Bibliographic record

VenueCanadian Geotechnical Journal · 2022
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsnot available
Fundersnot available
KeywordsConsolidation (business)GeotextileDewateringGeotechnical engineeringSlurryCompactionEngineeringParametric statisticsMathematicsEnvironmental engineering

Abstract

fetched live from OpenAlex

Introducing the prefabricated horizontal drains (PHDs) into the permeable geotextile tubes has been reckoned as an efficient and economical method of dewatering slurries with high water contents. However, its application is limited by the poor understanding of the fundamental consolidation mechanism, often resulting in overconservative designs. With the proposed two-dimensional plane-strain consolidation model, a semi-analytical solution calibrated by laboratory test results is obtained. Furthermore, parametric analyses, for example, PHD pave rate, and element aspect ratio, along with the soil anisotropy coefficient, are also conducted to achieve the optimum design requirement. A critical condition corresponding to the optimum effectiveness of this consolidation technique is found, beyond which the consolidation efficiency decreases gradually. The greater the abovementioned parameters are, the later and milder the efficiency reduction occurs. The consolidation efficiency can keep at a high level until the end of consolidation when the values of these parameters are great enough. In the end, design charts and design recommendations are provided with immediate benefits for practical engineers.

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 score0.485
Threshold uncertainty score0.727

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.170
Teacher spread0.164 · 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

Citations8
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicGeotechnical Engineering and Soil StabilizationFrench-language works237,207