MétaCan
Menu
Back to cohort
Record W3173884912 · doi:10.3390/mi12070786

Numerical and Experimental Investigations of Micro Thermal Performance in a Tube with Delta Winglet Pairs

2021· article· en· W3173884912 on OpenAlexaff
Jiangbo Wang, Ting Fu, Liangcai Zeng, Guang Chen, Fue‐Sang Lien

Bibliographic record

VenueMicromachines · 2021
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsUniversity of Waterloo
FundersWuhan University of Science and TechnologyWuhan UniversityNational Natural Science Foundation of China
KeywordsVortex generatorWingtip deviceNusselt numberHeat transfer enhancementVortexMaterials scienceHeat transfer coefficientHeat transferMechanicsThermalTurbulenceThermodynamicsHeat exchangerTube (container)Composite materialPhysicsReynolds number

Abstract

fetched live from OpenAlex

In this research, a novel vortex generator (VG) is presented. The experimental and numerical investigations were carried out to study the micro thermal-hydraulic performance in a heated tube. The numerical results showed that the fluid in the core flow region and the near-wall region was fully mixed because of the longitudinal vortices created by the vortex generators. In addition, the experimental results showed that the heat transfer coefficient (h) decreased with the increasing pitch ratio (PR) value, while the friction coefficient exhibited the opposite trend. With the increasing ration angle (RA) numbers, the h values decreased while the f numbers increased. In addition, the maximum and minimum values of the fraction ratio were 1.66 and 4.27, while these values of the Nusselt number ratio were 1.24 and 1.83. The maximum thermal enhancement factor (TEF) was 1.21 when PR = 0.5, RA = 0° and Re = 9090. The heat transfer enhancement mechanism of the vortex generator is explained from the microscopic point of view.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.287

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 head0.007
GPT teacher head0.196
Teacher spread0.189 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueMicromachinesSame topicHeat Transfer and OptimizationFrench-language works237,207