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Record W2464377621 · doi:10.1002/cjce.22579

Effective thermal conductivity of unary particulate bed

2016· article· en· W2464377621 on OpenAlexvenueno aff
D. Mandal, Shuplay Gupta

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicHeat and Mass Transfer in Porous Media
Canadian institutionsnot available
Fundersnot available
KeywordsPebbleThermal conductivityThermal conductionUnary operationMaterials scienceHeat transferParticle (ecology)ThermodynamicsMechanicsComposite materialPhysicsMathematics

Abstract

fetched live from OpenAlex

Abstract Effective thermal conductivity of a unary (mono‐sized) pebble bed depends on the physical properties of solid pebbles, physical properties and flow rate of fluid, temperature, coordination number of pebbles, and void fraction. The pebble size also plays an important role on the effective thermal conductivity of a unary pebble bed. To date, no theoretical justification for the same has been reported. In this present study an attempt was made to justify theoretically the dependence of the effective thermal conductivity on pebble size of a unary pebble bed filled with a stagnant fluid. A mathematical model has been developed to determine the effective thermal conductivity of a unary pebble bed with stagnant fluid. Different particle sizes (10 μm to 10 mm) were considered and modes of heat transfer were assumed to be conduction and convention only. Radiation mode of heat transfer was not considered. It was found that the effective thermal conductivity depends on the pebble size and the estimated values of the same were in close agreement with the reported experimental results.

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 score0.008
Threshold uncertainty score0.259

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 head0.007
GPT teacher head0.178
Teacher spread0.171 · 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

Citations18
Published2016
Admission routes1
Has abstractyes

Explore more

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