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Record W3091820945 · doi:10.3390/sym12101652

Thermo-Hydraulic Performance Analysis on the Effects of Truncated Twisted Tape Inserts in a Tube Heat Exchanger

2020· article· en· W3091820945 on OpenAlexafffund
Mehdi Ghalambaz, Ramin Mashayekhi, Hossein Arasteh, Hafız Muhammad Ali, Pouyan Talebizadehsardari, Wahiba Yaïci

Bibliographic record

VenueSymmetry · 2020
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsNatural Resources Canada
FundersNatural Resources Canada
KeywordsNusselt numberReynolds numberPressure dropMechanicsHeat exchangerMaterials scienceHeat transferHeat transfer coefficientHeat transfer enhancementConcentric tube heat exchangerTube (container)ThermodynamicsComposite materialPhysicsTurbulence

Abstract

fetched live from OpenAlex

This paper investigates the convective heat transfer in a heat exchanger equipped with twisted tape elements to examine effects of the twisted tape truncation percentage, pitch value, position and Reynolds number using 3D numerical simulation. A symmetric heat flux is applied around the tube as the studied heat exchanger. Based on the influences in both heat transfer enhancement and pressure drop, the performance evaluation criterion (PEC) is utilized. Inserting twisted tape elements and reducing the pitch value significantly augment the Nusselt number, friction coefficient and PEC number compared to the plain tube. For the best case with a Reynolds number of 1000, the average Nusselt number increases by almost 151%, which is the case of fully fitted twisted tape at a pitch value of L/4. Moreover, increasing the twisted tape truncation percentage reduces both heat transfer and pressure drop. Furthermore, the highest heat transfer rate is achieved when the truncated twisted tape is located at the entrance of the tube. Finally, it is concluded that for P = L, L/2, L/3 and L/4, the optimum cases from the viewpoint of energy conservation are twisted tapes with truncation percentages of 75, 50, 50 and 0%, in which the related PEC numbers at a Reynolds number of 1000 are almost equal to 1.08, 1.24, 1.4 and 1.76, respectively.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.193
Teacher spread0.184 · 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 source (direct Gemma or distilled Codex), 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

Citations31
Published2020
Admission routes2
Has abstractyes

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