MétaCan
Menu
Back to cohort
Record W2097262471 · doi:10.1504/ijhvs.2009.027133

Multi-objective shape optimisation of an automotive universal joint assembly

2009· article· en· W2097262471 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Heavy Vehicle Systems · 2009
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsQueen's University
Fundersnot available
KeywordsAutomotive industryJoint (building)Component (thermodynamics)EngineeringMachiningDomain (mathematical analysis)Volume (thermodynamics)Automotive engineeringMechanical engineeringStructural engineeringMathematical optimizationMathematicsAerospace engineering

Abstract

fetched live from OpenAlex

This research considered the multi-objective shape optimisation of an automotive universal joint. Optimisation was conducted at the component level and assembly level using a weighted sum of three objective functions: part volume, adjoining joint angle and machining cost. All measures of performance were competing objective functions (increasing joint angle required a corresponding increase in volume and cost). Results of the component level optimisation overestimated potential improvements when compared to the assembly level optimisation. Furthermore, optimum designs created at the component level were infeasible in the assembly level domain, thereby emphasising the importance of conducting design optimisation at the assembly level.

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.

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: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.433

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 communication0.0000.001
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 head0.016
GPT teacher head0.248
Teacher spread0.232 · 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