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Record W4396763185 · doi:10.1002/cjce.25303

Leakage characteristics of plug flow in the case of pipe leakage

2024· article· en· W4396763185 on OpenAlexvenueno aff
Tao Ren, Wenjun Ma, Jiangbei Huang, Zhiwei Li, Bin Sun

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsnot available
FundersNatural Science Foundation of Henan ProvinceHenan UniversityZhengzhou UniversityChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsLeakage (economics)Spark plugPlug flowLeakPetroleum engineeringEnvironmental scienceMechanicsMaterials scienceEngineeringMechanical engineeringPhysicsEnvironmental engineering

Abstract

fetched live from OpenAlex

Abstract In order to study the changes in two‐phase flow parameters after pipeline damage and the impact of gas injection on water leakage from damaged pipelines, experimental and simulation studies were conducted on the damaged pipelines. The main objective is to compare the void fraction in intact and damaged states and to investigate the factors influencing and variations in gas–liquid leakage flow rates. The results show that increasing the liquid superficial velocity can reduce the difference in void fraction distribution caused by different damage directions. The leakage flow rate is affected by the direction of damage and the superficial velocity of the respective phase. It has been discovered that gas injection in the pipeline can make it easier to find small‐area pipeline damage. The change rate of the volume void fraction shows different changes with the increase in gas proportion in different directions; the shape of the bubble has no bearing on this change.

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 score0.014
Threshold uncertainty score0.244

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 integrity0.0000.000
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 head0.006
GPT teacher head0.169
Teacher spread0.163 · 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

Citations5
Published2024
Admission routes1
Has abstractyes

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