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Record W4392760961 · doi:10.1002/apj.3056

Motion and interaction of in‐line bubbles in quiescent non‐aqueous solutions of hydrocarbon resin

2024· article· en· W4392760961 on OpenAlexaff
Mei Li, Denghan Luo, Zhongyao Zhang, Xiaopeng Chen, Lifang Huang, Jiezhen Liang, Xiaojie Wei, Bei Liu, Linlin Wang

Bibliographic record

VenueAsia-Pacific Journal of Chemical Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsPetro-Canada
FundersNational Natural Science Foundation of ChinaGuangxi Key Laboratory of Petrochemical Resource Processing and Process Intensification Technology, Guangxi UniversityInnovative Research Group Project of the National Natural Science Foundation of China
KeywordsBubbleDragCoalescence (physics)MechanicsAqueous solutionViscosityMaterials scienceChemistryChemical physicsPhysicsComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Hydrocarbon resin (HR) is an essential fine chemical. The preparation and application process of HR involves lots of gas–liquid heterogeneous reactions, and the bubbly flow behavior influences them significantly. Using high‐speed photography and digital image processing techniques, the motion and interaction of in‐line bubbles in non‐aqueous solutions of HR are examined in this article. The results show a critical gas flow rate that can change the bubbling regime. It can be observed that viscosity features prominently in changing the shape of bubbles and their motion. As the viscosity increases, the bubbles are more prone to coalescence, and the bubble coalescence process gradually changes from connected slip‐rising coalescence to connected‐rising coalescence. The viscosity transition region between non‐coalescent and coalescent systems in non‐aqueous solutions of HR occurs at 3.6–9.2 mPa·s. Further, a force analysis shows that in paired bubbles, the leading bubble can be viewed as an individual bubble unaffected by trailing bubble before the two bubbles collide, but in the wake of the leading bubble, the drag force on the trailing bubble decreases and the added mass force increases.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.627
Threshold uncertainty score0.449

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 head0.005
GPT teacher head0.197
Teacher spread0.192 · 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 designBench or experimental
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

Citations0
Published2024
Admission routes1
Has abstractyes

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