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Record W4386072869 · doi:10.11159/htff23.164

Combined Natural Convection and Radiative Heat Transfer from a Horizontal Helical Coil Placed on the Ground and in Air: A Comparative Study

2023· article· en· W4386072869 on OpenAlexvenueno aff
Gloria Biswal, Sukanta Kumar Dash

Bibliographic record

VenueProceedings of the World Congress on Mechanical, Chemical, and Material Engineering · 2023
Typearticle
Languageen
FieldEnergy
TopicSolar Thermal and Photovoltaic Systems
Canadian institutionsnot available
Fundersnot available
KeywordsNatural convectionElectromagnetic coilRadiative transferConvectionHeat transferMechanicsRadiant heatEnvironmental scienceMaterials sciencePhysicsOpticsElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

The current work presents a comparative analysis of natural convection and radiation heat transfer from a solid isothermal helical coil either placed on the ground or suspended in the air.Numerical simulations are carried out in the range of Rayleigh number ( ), surface emissivity ( )≤ ≤ , geometrical parameters of the helical-coil, like diameter of the coil ( ), and pitch ( ). A graphic representation of the effects of geometrical parameters on heat transfer characteristics has been depicted, including average Nu, relative convection and radiation rates, and temperature contours.Radiation heat transfer is modeled using the S2S radiation model.A helical-coil in the air always has a higher average Nu than one on the ground.It is found that with an increase in D/d, the heat loss from the coil rises for all p/d and Ra because the coil opening area on either side of the helical coil expands, providing less resistance to the core flow.When the coil is on the ground, and when D/d varies from 8 to 24, the relative strength of Qc rises by 2% and 1.07% for p/d=7.5 and 3 respectively at Ra=10 4 .

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 score0.010
Threshold uncertainty score0.623

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 head0.013
GPT teacher head0.216
Teacher spread0.202 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

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