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Record W1579057521

Numerical characterisation of nonlinear stiffness properties of pre-stressed vibration isolation mounts

2002· article· en· W1579057521 on OpenAlexaffvenue
D. C. Stredulinsky, Jeffrey P. Szabo, M.W. Chernuka

Bibliographic record

VenueCanadian acoustics · 2002
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsMartec (Canada)
Fundersnot available
KeywordsVibration isolationStiffnessVibrationNonlinear systemStructural engineeringFinite element methodViscoelasticityStiffness matrixNumerical analysisMatrix (chemical analysis)Materials scienceEngineeringAcousticsMathematicsPhysicsComposite materialMathematical analysis
DOInot available

Abstract

fetched live from OpenAlex

Numerical characterisation of nonlinear stiffness properties of pre-stressed vibration isolation mounts was presented. A computational procedure was developed to evaluate the condensed stiffness matrix of vibration isolators required by the vibration of viscoelastic and elastic structures (VVES) program. The procedure was based on a nonlinear finite element program which is able to handle complicated mount geometry and nonlinear effect associated with the static pre-loading. Three practical vibration isolation mount structures were analyzed and satisfactory numerical results were obtained.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.184
Teacher spread0.170 · 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
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
Published2002
Admission routes2
Has abstractyes

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