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Record W4410503238 · doi:10.1177/10812865251336256

A refined analytical model for acoustic waves in elastic fiber composites

2025· article· en· W4410503238 on OpenAlexafffund
C. Q. Ru, Peter Schiavone

Bibliographic record

VenueMathematics and Mechanics of Solids · 2025
Typearticle
Languageen
FieldEngineering
TopicComposite Material Mechanics
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComposite materialMaterials scienceFiber

Abstract

fetched live from OpenAlex

Unidirectional fiber-reinforced composites continue to gain increasing importance in industrial applications particularly in the area of dynamic behavior. Many studies have focused on the determination of wave speed and attenuation of propagating waves in elastic fiber composites. These studies, however, most often use methods which are overly complicated and computationally expensive. Recently, a simple yet effective medium model was developed which provides explicit formulas for the dynamic behavior of P-waves, SV-waves and SH-waves. This model, however, failed to accurately predict the dynamic behavior of fiber-reinforced composites at higher frequencies around and beyond the bandgap region. In the present study, a refined analytical model is presented which supplements the aforementioned model with wave radiation damping. Our results show that the explicit formulas given by the present model are in good agreement with known numerical results in the literature for P-waves, SV-waves, and SH-waves.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.781
Threshold uncertainty score0.622

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 head0.014
GPT teacher head0.242
Teacher spread0.229 · 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
Published2025
Admission routes2
Has abstractyes

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