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Record W2418169391 · doi:10.1139/tcsme-2009-0047

GEOMETRIC SYNTHESIS OF PLANAR 3-<i>R<u>P</u>R</i> PARALLEL MECHANISMS FOR SINGULARITY-FREE WORKSPACE

2009· article· en· W2418169391 on OpenAlexafffundvenue
Qimi Jiang, Clément Gosselin

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2009
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWorkspaceSingularityOrientation (vector space)Equilateral trianglePlanarGeometryMathematicsGravitational singularityTopology (electrical circuits)Mathematical analysisCombinatoricsComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

This work focuses on the geometric synthesis of planar 3-RPR parallel mechanisms in order to guarantee a singularity-free workspace for a desired orientation range. The effects of the orientation angle, the minimal leg length as well as the base shape on the singularity-free workspace are analyzed using the Gauss divergence theorem. The results show that for every orientation angle, there exists an optimal minimal leg length which leads to the maximal singularity-free workspace. If the optimal minimal leg lengths are used, the equilateral triangle base yields the maximal singularity-free workspace for any orientation angle. However, for a prescribed working range of the orientation angle, the optimal minimal leg length may be different from the individual optimal minimal leg lengths. Based on the optimal minimal leg length determined for a prescribed working range of the orientation angle, a geometric synthesis procedure is proposed in order to guarantee a singularity-free workspace.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.008
GPT teacher head0.185
Teacher spread0.177 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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
Published2009
Admission routes3
Has abstractyes

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