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Record W2594264715

Haptic Simulation of Linear Elastic Media with Fluid Inclusions

2005· article· en· W2594264715 on OpenAlexaff
Andrew H. Gosline, Septimiu E. Salcudean, J. Yan

Bibliographic record

VenueResearchWorks at the University of Washington (University of Washington) · 2005
Typearticle
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHaptic technologyFinite element methodMechanicsFluid–structure interactionHydrostatic equilibriumDeformation (meteorology)Matrix (chemical analysis)Computer scienceMaterials scienceSimulationPhysicsEngineeringStructural engineeringComposite material
DOInot available

Abstract

fetched live from OpenAlex

We present a fast technique for simulating fluid-filled elastic objects with the Finite Element Method. By simulating the presence of fluid with hydrostatic fluid pressure, a quasi-static simulation of fluid can be achieved by applying a force boundary condition to the nodes on the fluid-elastic interface. Using a proportional feedback control algorithm, a relationship between the volume and pressure of the fluid structure can be maintained. Optimal parameters for the control algorithm are found by determining the response of the of the elastic system to changes in pressure. This approach has been shown to agree with experimental deformation data taken from a fluid-filled gelatin phantom. Combining linear FEM methods with matrix condensation techniques and the tuned proportional feedback control allows for the simulation of a fluid-filled elastic object at real time haptic update rates.

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: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.712

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.015
GPT teacher head0.215
Teacher spread0.200 · 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

Citations7
Published2005
Admission routes1
Has abstractyes

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