MétaCan
Menu
Back to cohort
Record W3184343066 · doi:10.1002/cjce.24267

Numerical simulation of nanofluids forced convection in a corrugated double‐pipe heat exchanger

2021· article· en· W3184343066 on OpenAlexvenueno aff
Zi Ding, Cong Qi, Tao Luo, Yuxing Wang, Jianglin Tu, Chengchao Wang

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicNanofluid Flow and Heat Transfer
Canadian institutionsnot available
FundersNatural Science Foundation of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsNanofluidMaterials scienceHeat exchangerShell and tube heat exchangerPlate heat exchangerHeat transferConcentric tube heat exchangerMicro heat exchangerThermodynamicsPlate fin heat exchangerHeat pipeMechanicsPhysics

Abstract

fetched live from OpenAlex

Abstract In this study, the heat transfer and flow characteristics of TiO 2 ‐H 2 O nanofluids with TiO 2 mass fractions of 0.0, 0.1, 0.3, and 0.5 wt.% in corrugated and smooth double‐pipe heat exchangers were compared using numerical simulations. The results demonstrated that TiO 2 ‐H 2 O nanofluids effectively enhanced the heat transfer compared to deionized water, and that the heat exchange capacity gradually increased with the TiO 2 mass fraction. The corrugated pipe heat exchanger disturbed the fluid flow on both the shell side and pipe side, breaking the boundary layer and creating vortices in the corrugated zone. This provided a higher heat transfer capability than the smooth double‐pipe heat exchanger, but also increased the fluid flow resistance in the pipe. In general, the use of nanofluids and corrugated pipes was found to significantly improve the heat transfer efficiency of the double‐pipe heat exchanger.

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 score0.189
Threshold uncertainty score0.441

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 head0.012
GPT teacher head0.202
Teacher spread0.190 · 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

Citations16
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicNanofluid Flow and Heat TransferFrench-language works237,207