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Record W2573896095 · doi:10.1139/tcsme-2008-0020

EFFECTS OF BRAKE DISC GEOMETRICAL PARAMETERS AND CONFIGURATIONS ON AUTOMOTIVE BRAKING THERMAL PERFORMACE

2008· article· en· W2573896095 on OpenAlexaffvenue
Zhongzhe Chi, G.F. Naterer, Yuping He

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicBrake Systems and Friction Analysis
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsPillarDisc brakeAutomotive industryThermalAerodynamicsRotor (electric)BrakeParametric statisticsAutomotive engineeringMechanicsFlow (mathematics)Brake padMechanical engineeringMaterials scienceEngineeringAerospace engineeringPhysicsMathematics

Abstract

fetched live from OpenAlex

This paper examines the effects of geometrical parameters of pillar post rotors on the thermal performance of automotive vehicle brakes. The thermal performance of vented disc brakes strongly depends on the aerodynamic characteristics of the air flow through the rotor passages. These air flow passages are determined by the geometrical parameters of the brake rotors. In this study, different pillar post rotor models are considered and the corresponding numerical simulations are performed, in order to investigate the effects of various geometrical parameters on the thermal performance. These geometrical parameters include the shape, size, and distribution of a pillar post. The new insight from these parametric studies provides useful guidelines to optimize the geometry of pillar post rotors of automotive vehicles.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.009
GPT teacher head0.178
Teacher spread0.169 · 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 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
Published2008
Admission routes2
Has abstractyes

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