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Record W4237046884 · doi:10.1115/1.862ama_ch7

Modeling and Experimentation of Temperature Calculations for Belt Drive Transmission Systems in the Aviation Industry

2021· book-chapter· en· W4237046884 on OpenAlexaff
Xingchen Liu, Kamran Behdinan

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAviationTransmission (telecommunications)Automotive engineeringEngineeringAeronauticsAerospace engineeringMechanical engineeringElectrical engineering

Abstract

fetched live from OpenAlex

The belt drive system is a common but critical transmission component in helicopter transmission systems [1]. This system depicted in Figure 7.1 consists of driver (DR) and driven (DN) pulleys. It transmits power from the engine to the gearbox of the propeller. Traditionally, pulleys in this type of system are made of steel for high-torque transmissions. However, a novel type of fiber-reinforced polymer (FRP) could potentially be used for pulley fabrication, due to its favorable strength-to-weight ratio. However, its application in the aviation industry is not straightforward. The low thermal conductivity of FRP causes surface deterioration in the pulleys and belt, reducing the life of the system. To improve reliability, surface temperature profiles must be acquired in advance, especially during the design stage. Therefore, in order to avoid this type of failure, this study proposes a thermal model that provides immediate temperature distributions for belt drive system design.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.920
Threshold uncertainty score0.511

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 integrity0.0010.000
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 head0.018
GPT teacher head0.249
Teacher spread0.231 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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