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Record W4401931151 · doi:10.1016/j.ijft.2024.100830

Numerical evaluation of the impact of using spiral innovative turbulator on improving the thermal performance of a helical double-pipe heat exchanger

2024· article· en· W4401931151 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Thermofluids · 2024
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsTurbulatorSpiral (railway)Heat exchangerMechanicsThermalMaterials scienceMechanical engineeringEngineeringThermodynamicsReynolds numberPhysicsTurbulence

Abstract

fetched live from OpenAlex

Due to the necessity of performing thermal operations, heat exchangers are widely employed in many different areas. The heat transfer and fluid flow within a spiral double-pipe heat exchanger fitted with a novel turbulator were numerically assessed in this work. The presented novel turbulator is a curved tube with holes incorporated into its thickness and spiral ribs on its inner wall. The turbulator wall's curved rib design produces secondary flows at the turbulator output when fluid flows through the tube and the perforations. A commercial CFD tool, based on the finite volume technique, was used to conduct the numerical simulations. The fluid flow regime is turbulence (Re = 8,000 – 14,000). Two sections make up this work. The first portion looked at how the hydrothermal behavior of the fluid flow inside the proposed turbulator was affected by the angle at which the curved ribs rotated. For this angle, three values were considered: θ = 30, 90, and 150°, and the outcomes were contrasted with those of a plain spiral double-tube heat exchanger (turbulator not included). Then, the number of embedded holes in the turbulator's thickness changes in the second part, and three values of N = 12, 16, and 20 were considered. According to the first part's findings, the model exhibiting θ = 90° had a greater thermal performance factor at Re = 10,000. This model has a more noteworthy thermal performance factor than the models with θ = 150 and θ = 30° by approximately 15.62 % and 22.65 %, respectively (at Re = 10,000). Furthermore, the second section's numerical findings showed that the model with N = 20 had more extraordinary thermal performance at Re = 10,000. Model N = 20 has a thermal performance factor of about 16.93 % and 17.55 % greater than models N = 16 and N = 12. Within the proposed heat exchanger, the recommended turbulator produced a sizable rotating flow, and including embedded holes significantly reduced the pressure drop this kind of turbulator causes.

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.

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)0.001
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 score0.287
Threshold uncertainty score0.333

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.041
GPT teacher head0.318
Teacher spread0.277 · 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