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Record W2134498742 · doi:10.1109/robot.1998.677216

Multirate haptic simulation achieved by coupling finite element meshes through Norton equivalents

2002· article· en· W2134498742 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Council
KeywordsPolygon meshFinite element methodComputationComputer scienceCoupling (piping)Haptic technologyComputational scienceMesh generationVolume meshSimulationAlgorithmComputer graphics (images)Structural engineeringMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

This paper introduces a methodology to simulate the dynamics of deformable viscoelastic 3D bodies in real-time for haptic interaction. The method is based upon a finite element approach. The central idea in this scheme is to reduce the computation required in regions which are to the periphery of the region of interaction between the virtual haptic device and the virtual body. This is accomplished by implementing a multilayer finite element mesh. The top layer, or parent, consists of a coarse mesh of the entire body; child meshes represent sub-regions of the coarse mesh, but have a much finer resolution. By using equivalent impedances to relate the two meshes, it is possible to decouple the coarse and fine regions; this enables the system to not only to have different resolutions in different regions, but also allows the parent and child meshes to be updated at different frequencies. The multilayer mesh also addresses numerical integration issues.

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 categoriesInsufficient payload (model declined to judge)
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 score0.599
Threshold uncertainty score1.000

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.043
GPT teacher head0.252
Teacher spread0.210 · 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

Quick stats

Citations99
Published2002
Admission routes2
Has abstractyes

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