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Record W4386207852 · doi:10.1139/cgj-2022-0370

Combined vacuum-assisted geotextile and geomembrane tubes for sludge dewatering: a theoretical switching point

2023· article· en· W4386207852 on OpenAlexvenueno aff
Hao Zhang, Honglei Sun, Sijie Liu, Xueyu Geng, Yongfeng Deng, Yuanqiang Cai

Bibliographic record

VenueCanadian Geotechnical Journal · 2023
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsGeotextileGeomembraneDewateringConsolidation (business)Geotechnical engineeringTube (container)CompactionMaterials scienceEngineeringWaste management

Abstract

fetched live from OpenAlex

Treating the high water-content sludge with vacuum-assisted prefabricated horizontal drains (PHDs) placed inside, geotextile tubes have the advantage of multiple drainage paths, and geomembrane tubes have the superiority of high vacuum maintenance. Therefore, converting the geotextile tube into a geomembrane tube during slurry dewatering is an effective measure for greater dewatering efficiency and better dehydration effect. In this study, a profound plane-strain consolidation model considering two-dimensional seepage is developed for explaining the dewatering mechanism of sludge in the geo-tubes. Analytical solutions are given and validated by the experiment. The impact of major variables on tube efficiency is further discussed to reference the practice design. Parametric analyses reveal the critical time corresponding to the optimal efficiency of the geotextile tube, after which its consolidation efficiency decreases significantly. However, the consolidation efficiency of a geomembrane tube increases throughout the duration. Consequently, a switching point corresponding to the iso-efficiency state of the geotextile tube and geomembrane tube can be determined for the tube conversion.

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)0.000
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 score0.129
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.009
GPT teacher head0.202
Teacher spread0.193 · 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

Citations7
Published2023
Admission routes1
Has abstractyes

Explore more

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