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Record W1480967660 · doi:10.4271/2005-01-2413

Consideration of Static-Strain-Dependent Dynamic Complex Modulus in Dynamic Stiffness Calculation of Mount/Bushing by Commercial Finite Element Codes

2005· article· en· W1480967660 on OpenAlexaff
Yun-Ho Shin, Hojung Lee, Kwang-Joon Kim

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2005
Typearticle
Languageen
FieldEngineering
TopicElasticity and Material Modeling
Canadian institutionsNovelis (Canada)
Fundersnot available
KeywordsBushingFinite element methodStiffnessStructural engineeringModulusDynamic modulusStrain (injury)Materials scienceEngineeringDynamic mechanical analysisComposite material

Abstract

fetched live from OpenAlex

<div class="htmlview paragraph">Little attention has been paid to static-strain-dependence of dynamic complex modulus of viscolelastic materials so far. Hence, current commercial Finite Element Method(FEM) codes do not take such characteristics into consideration in constitutive equations of viscoelastic materials. Recent experimental observations that static-strain-dependence of dynamic complex modulus of viscolelastic materials, especially filled rubbers, are significant, however, require that solutions somehow are necessary. In this study, a simple technique of using a commercial FEM code, ABAQUS, is introduced, which seems to be far more cost/time saving than development of a totally new software with such capabilities. A correction factor is used to reflect the influence of static-strains in Morman model, which is the base of the ABAQUS. The proposed technique is applied to viscoelastic components of rather complicated shape to predict the dynamic stiffness under static-strain and the predictions are compared with experimental results.</div>

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.252
Teacher spread0.239 · 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.

Study designObservational
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

Citations1
Published2005
Admission routes1
Has abstractyes

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