MétaCan
Menu
Back to cohort
Record W4386082892 · doi:10.11159/htff23.141

Experiment on Heat Transfer Enhancement for a Double Pipe Heat Exchanger with Air Injection of Perforated Turbulator

2023· article· en· W4386082892 on OpenAlexvenueno aff
Ali A. Abdulrasool, Muhsen M. Al-Silbi, Abdalrazzaq K. Abbas, Mohammed Wahhab Aljibory

Bibliographic record

VenueProceedings of the World Congress on Mechanical, Chemical, and Material Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsnot available
FundersUniversity of Kerbala
KeywordsTurbulatorMaterials scienceHeat transferHeat exchangerHeat transfer enhancementMechanicsMechanical engineeringTurbulenceHeat transfer coefficientEngineeringReynolds numberPhysics

Abstract

fetched live from OpenAlex

In this study, an attempt is made to evaluate the performance of a double pipe heat exchanger (DPHE) through an experiment. The outside surface of the inner pipe of the DPHE is surrounded with perforated helical tube, where the perforations allow air to enter the annulus. The air injection and the turbulator itself are expected to increase the number of vortices in the boundary layer of the inner pipe (annulus side) and expand the heat transfer regions. Due to the bouncy effect, the small air bubbles within the cold water promote flow eddies and hence increase the thermal performance. The Reynolds number based on the hydraulic diameter of the annulus is ranged from 5,000 to 17,000. The findings demonstrate that for a flow affected by an air injector, performance varies with Reynolds number. Both the Nusselt number and efficiency increase percentages are approximately 27 for each. However, the friction factor raises to 43% compared to the plain case, which only increases the performance evaluation criteria (PEC) by 8%.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.010
GPT teacher head0.210
Teacher spread0.200 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the World Congress on Mechanical, Chemical, and Material EngineeringSame topicHeat Transfer and OptimizationFrench-language works237,207