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Record W1975026089 · doi:10.1115/1.1755691

Development of a Finite Element Cable Model for Use in Low-Tension Dynamics Simulation

2004· article· en· W1975026089 on OpenAlexaff
Bradley J. Buckham, Frederick Driscoll, Meyer Nahon

Bibliographic record

VenueJournal of Applied Mechanics · 2004
Typearticle
Languageen
FieldEngineering
TopicVibration and Dynamic Analysis
Canadian institutionsMcGill UniversityUniversity of Victoria
Fundersnot available
KeywordsFinite element methodDiscretizationTension (geology)Equations of motionBendingConvergence (economics)Constraint (computer-aided design)Structural engineeringDynamics (music)Computer scienceRepresentation (politics)Mixed finite element methodExtended finite element methodMethod of mean weighted residualsApplied mathematicsMathematicsMathematical analysisEngineeringGeometryPhysicsClassical mechanicsGalerkin methodAcoustics

Abstract

fetched live from OpenAlex

To accurately simulate the motion of slack marine cables, it is necessary to capture the effects of the cable’s bending and torsional stiffness. In this paper, a computationally efficient and novel third-order finite element is presented that provides a representation of both the bending and torsional effects and accelerates the convergence of the model at relatively large element sizes. Using a weighted residual approach, the discretized motion equations for the new cubic element are developed. Applying inter-element constraint equations, we demonstrate how an assembly of these novel elemental equations can be significantly reduced to prevent the growth of the system equations normallly associated with such higher order elements and allow for faster evaluation of the cable dynamics in either taut or low-tension situations.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.017
GPT teacher head0.224
Teacher spread0.207 · 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 designSimulation or modeling
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

Citations101
Published2004
Admission routes1
Has abstractyes

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