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Record W4405430143 · doi:10.1016/j.cja.2024.103347

Wave-based approaches for wavespace of highly contrasted structures with viscoelastic damping

2024· article· en· W4405430143 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChinese Journal of Aeronautics · 2024
Typearticle
Languageen
FieldEngineering
TopicStructural Analysis of Composite Materials
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaCentre Lyonnais d'Acoustique, Université de LyonUniversité de LyonAgence Nationale de la Recherche
KeywordsViscoelasticityMaterials scienceStructural engineeringEngineeringComposite material

Abstract

fetched live from OpenAlex

The present study investigates the wavespace of Highly Contrasted Structures (HCS) and Highly Dissipative Structures (HDS) by wave-based models. The Asymptotic Homogenization Method (AHM), exploits the asymptotic Zig-Zag model and homogenization technique to compute the bending wavenumbers via a 6th-order equation. The General Laminate Model (GLM) employs Mindlin’s displacement field to establish displacement-constraint relationships and resolves a quadratic Eigenvalue Problem (EVP) of the dispersion relation. The Wave Finite Element (WFE) scheme formulates the Nonlinear Eigenvalue Problem (NEP) for waves in varying directions and tracks complex wavenumbers using Weighted Wave Assurance Criteria (WWAC). Two approaches are introduced to estimate the Damping Loss Factor (DLF) of HDS, with the average DLF calculated by the modal density at various angles where non-homogeneity is present. Evaluation of robustness and accuracy is made by comparing the wavenumbers and DLF obtained from AHM and GLM with WFE. WFE is finally extended to a sandwich metastructure with a non-homogeneous core, and the Power Input Method (PIM) with Finite Element Method (FEM) data is employed to assess the average DLF, demonstrating an enhanced DLF compared to layered configurations with the same material portion, indicating increased energy dissipation due to the bending-shear coupling effects.

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.

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 score0.126
Threshold uncertainty score0.599

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 integrity0.0000.000
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 head0.019
GPT teacher head0.229
Teacher spread0.210 · 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