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Record W1993446688 · doi:10.1002/cjce.20690

A novel method to improve the efficiency of a cooking device via thermal insulation

2011· article· en· W1993446688 on OpenAlexvenueaboutno aff
Arijit A. Ganguli, Ajitkumar S. Gudekar, Aniruddha B. Pandit, Jyeshtharaj B. Joshi

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2011
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsnot available
FundersUniversity Grants Commission
KeywordsMaterials scienceTransient (computer programming)Thermal insulationHeat transfer coefficientThermalRayleigh scatteringReduction (mathematics)Composite materialMechanicsHeat transferThermodynamicsOpticsMathematicsComputer scienceGeometryPhysics

Abstract

fetched live from OpenAlex

Abstract We propose a method of finding the transient temperature variation in an insulated cooking device. We also report a means of optimising the thickness of insulation. The cooking device is a double walled cylindrical vessel with spacing of 5–20 mm between the vertical walls (width) and spacing of 560 or 870 mm between top and bottom surfaces (height). The height to width ratio ( H / L ) is between 28 and 174 and Rayleigh number ( Ra ) is between 907 and 2.61 × 10 5 . First, an energy balance for the cooking device is established. A correlation is developed to predict the heat transfer coefficient (HTC) as a function of Ra and H / L . The method developed for finding the transient variation in temperature has been tested on two cooking device volumes: 120 and 700 lit. Using the optimised parameters, a reduction in heat loss of 22% and 30%, respectively, is observed. © 2011 Canadian Society for Chemical Engineering

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: none
Teacher disagreement score0.678
Threshold uncertainty score0.250

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 head0.200
Teacher spread0.187 · 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

Citations2
Published2011
Admission routes2
Has abstractyes

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