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Record W1974325100 · doi:10.1115/imece2008-67096

Nodal Position Finite Element Method and its Application to Dynamics of Cable Systems

2008· article· en· W1974325100 on OpenAlexafffund
Zheng Zhu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics Simulations and Interactions
Canadian institutionsYork University
FundersOntario Centres of Excellence
KeywordsFinite element methodBenchmark (surveying)Position (finance)Displacement (psychology)Computer scienceRotation (mathematics)Deformation (meteorology)Structural engineeringControl theory (sociology)EngineeringPhysicsGeology

Abstract

fetched live from OpenAlex

The current approaches to the design of the handling of towed cable systems onboard surface ships rely heavily on empirical methods and time-consuming/expensive prototype testing. This paper presents a new nodal position finite element method (FEM) as a design tool to simulate the dynamics of towed body system effectively. By solving for the position of cable directly instead of indirectly via the displacement, the new FEM does not need to decouple the elastic deformation from the rigid body rotation and thus eliminates the error source arising from the linearized incremental approximation in existing FEM. Analysis results demonstrate the new FEM algorithm is simple and robust by comparing with numerical benchmark test and experiments including sea trial data.

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: none
Teacher disagreement score0.936
Threshold uncertainty score0.232

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)0.0000.000

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 head0.009
GPT teacher head0.248
Teacher spread0.240 · 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

Citations2
Published2008
Admission routes2
Has abstractyes

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