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Record W2799923052 · doi:10.1139/tcsme-2004-0041

TIME-DOMAIN RESPONSE OF DAMPED LINEAR STRUCTURES USING FIRST-ORDER GHM FINITE ELEMENTS

2004· article· en· W2799923052 on OpenAlexaffvenue
D. J. McTavish

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2004
Typearticle
Languageen
FieldEngineering
TopicStructural Health Monitoring Techniques
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsViscoelasticityRepresentation (politics)Simple (philosophy)Time domainFrequency domainComputer scienceApplied mathematicsMathematicsMathematical analysisPhysics

Abstract

fetched live from OpenAlex

The use of “GHM” finite-elements is a technique that can be used to incorporate general linear viscoelastic behaviour, i.e., general linear material dynamic behaviour including damping, into time-domain structural dynamics models. The original second-order form of the method has been published previously. This paper introduces the use of the first-order form of the GHM method. This first-order form and its second-order predecessor enable and encourage the incorporation of measured material linear viscoelastic properties. The constant coefficient form necessary for state-space methods is retained, while additional coordinates are added to represent the material properties. The use of a selectable number of modulus function terms allows arbitrarily good representation of general viscoelastic behaviour over a given spectrum of known material response. The method is applied to a prototype shock response problem for illustration. This class of problem is significant in that the excitation and therefore the dynamic response is “broadband”. A model that incorporates material damping must be similarly broadband in its representation of material behaviour, otherwise the model will be incapable of producing a consistent prediction of structural response. In the sample problem, the GHM model is applied to actual viscoelastic material whose behaviour is neither simple viscous nor simple hysteretic.

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 score0.232
Threshold uncertainty score0.739

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 head0.016
GPT teacher head0.253
Teacher spread0.237 · 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

Citations1
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicStructural Health Monitoring TechniquesFrench-language works237,207