MétaCan
Menu
Back to cohort
Record W2027387523 · doi:10.2514/6.2007-7825

Three Dimensional Numerical Solution of Heat Transfer in a Honeycomb Cell

2007· article· en· W2027387523 on OpenAlexaff
Anthony O. Ives, Jian Wang, Srinivasan Raghunathan, Emmanuel Bénard, Patrick Sloan

Bibliographic record

Venue7th AIAA ATIO Conf, 2nd CEIAT Int'l Conf on Innov and Integr in Aero Sciences,17th LTA Systems Tech Conf; followed by 2nd TEOS Forum · 2007
Typearticle
Languageen
FieldEngineering
TopicFlow Measurement and Analysis
Canadian institutionsBombardier (Canada)
Fundersnot available
KeywordsHoneycombHeat transferMaterials scienceMechanicsComputer scienceComposite materialPhysics

Abstract

fetched live from OpenAlex

Bias acoustic liners have been investigated by a number of researchers and demonstrated to have acoustic benefits. However while research has concentrated on the acoustic aspects of the liner, little research has directly investigated its heat transfer properties. A three dimensional numerical investigation of the fluid flow and heat transfer properties of a single honeycomb cell was carried out in order to develop an understanding of the flow and heat transfer properties of the bias acoustic liner. Experimental measurements of fluid flow and heat transfer properties of an acoustic liner sample were also carried out in order to validate the numerical solution. The experimental results were found to give lower values of heat transfer coefficient at low flow rates when compared with the numerical solution. The numerical solution for pressure loss agreed with Kutscher’s findings. The experimental results agreed with the traditional expression for pressure loss across abrupt expansions.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.012
GPT teacher head0.217
Teacher spread0.205 · 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 designSimulation or modeling
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

Citations3
Published2007
Admission routes1
Has abstractyes

Explore more

Same venue7th AIAA ATIO Conf, 2nd CEIAT Int'l Conf on Innov and Integr in Aero Sciences,17th LTA Systems Tech Conf; followed by 2nd TEOS ForumSame topicFlow Measurement and AnalysisFrench-language works237,207