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Record W2072855269 · doi:10.1115/detc2002/dac-34066

Use of Constrained Viscoelastic Layers in the Design of Satellite Panels to Predict the Amplification Factor

2002· article· en· W2072855269 on OpenAlex
Marie-Jose ́e Potvin, André Côté, Éric Charbonneau, Maria-Elena Aguilar

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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStructural Analysis and Optimization
Canadian institutionsSte. Anne's HospitalCanadian Space Agency
Fundersnot available
KeywordsViscoelasticityLoss factorAmplification factorEigenvalues and eigenvectorsSatelliteFinite element methodDamping factorStructural engineeringComputer scienceMaterials sciencePhysicsEngineeringAerospace engineeringBandwidth (computing)

Abstract

fetched live from OpenAlex

A critical aspect of the design of a space structure is the prediction of the amplification factor. This factor is often estimated from comparison with similar structures, which can lead to costly errors. Adding viscoelastic patches enables an accurate prediction of the damping level of the structure since the viscoelastic patches become the main cause of damping for the structure. In this project, a test panel similar to large satellite feed panels is damped using five small viscoelastic patches. The location of the patches is optimized using the strain energy method. The amplification factor is obtained through a complex eigenvalue finite element analysis. The complex eigenvalue method is shown to be as accurate as the direct frequency analysis, but it runs much faster. The predicted amplification factor is within 15% of the experimental value which is a very good estimation for such a complex structure.

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 score0.347
Threshold uncertainty score0.169

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 head0.070
GPT teacher head0.219
Teacher spread0.149 · 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

Quick stats

Citations0
Published2002
Admission routes1
Has abstractyes

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