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Record W3011936996 · doi:10.3390/en13051291

Transient Natural Convection in a Thermally Insulated Annular Cylinder Exposed to a High Temperature from the Inner Radius

2020· article· en· W3011936996 on OpenAlexaff
A. A. Mohamad, Jan Taler, Paweł Ocłoń

Bibliographic record

VenueEnergies · 2020
Typearticle
Languageen
FieldEnergy
TopicSolar Thermal and Photovoltaic Systems
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsNatural convectionMechanicsHeat transferConvectionThermal energy storageRayleigh numberMaterials scienceThermodynamicsCylinderConvective heat transferThermalMechanical engineeringPhysicsEngineering

Abstract

fetched live from OpenAlex

Extensive numerical analysis was performed for the unsteady state, natural convection in the annular cylinders. The cylinder’s boundaries were thermally insulated, except the inner surface. The fluid (water) in the cylinder initially was assumed at a cold temperature while the inner surface was subjected to a high temperature. The time history for the heat transfer by diffusion and advection was studied. The time needed for fully charging the storage tank and rate of heat transfer was calculated. The predicted results were compared with the pure heat diffusion process and with a steady-state convection system. Therefore, CFD simulations were performed for natural convection in the storage tank. The main objective of this study was to establish correlations for the rate of heat transfer as a function of time and other controlling parameters. The correlation is needed in designing a thermal energy storage system for domestic and industrial heating processes. One of the drawbacks of the conventional thermal storage systems is the slow charging and discharging, where the heat transfer is mainly diffusion dominated. To overcome such a problem, a system was designed based on the natural convective heat transfer mechanism. Therefore, the heat transfer and fluid flow in a cylindrical storage tank were simulated for a range of Rayleigh numbers (104 to 108) and radius ratio. It was found that a convection-operated storage tank reduces the thermal charging process time drastically compared with the thermally diffusion charging process. The rate of reduction in the charging time mainly depends on the rate of heating and geometric parameter of the tank. To the best of the authors’ knowledge, the work is novel.

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 score0.273
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.197
Teacher spread0.185 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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