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Record W1998328548 · doi:10.1155/2009/538731

Analytical and Experimental Study Using Output‐Only Modal Testing for On‐Orbit Satellite Appendages

2009· article· en· W1998328548 on OpenAlexaff
Mashiul Alam, Ramin Sedaghati, Y. Soucy, Rama Bhat

Bibliographic record

VenueAdvances in Acoustics and Vibration · 2009
Typearticle
Languageen
FieldEngineering
TopicStructural Health Monitoring Techniques
Canadian institutionsCanadian Space AgencyConcordia University
Fundersnot available
KeywordsModalSatelliteModal testingAerospaceOrbit (dynamics)Modal analysisEngineeringAerospace engineeringShock (circulatory)Measure (data warehouse)Computer scienceStructural engineeringFinite element methodMaterials science

Abstract

fetched live from OpenAlex

Output‐only modal testing is an effective technique to identify the modal parameters of structural systems under ambient or operational conditions and has potential applications in civil, mechanical, and aerospace engineering. It may effectively be used for model validation, model updating, quality control, and health monitoring through the determination of modal characteristics of the structures. This approach to modal testing has great potential for ground and on‐orbit modal testing of space hardware, especially for flexible structures such as membrane payloads where the operating and ambient excitations, such as firing of AC thrusters and ambient thermal shock, are difficult or impossible to measure. The main objective of this work is to conduct analytical and experimental study on output‐only modal testing and to demonstrate its potential application to effectively extract modal parameters of an on‐orbit satellite appendage.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.038
GPT teacher head0.359
Teacher spread0.322 · 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 designBench or experimental
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

Citations2
Published2009
Admission routes1
Has abstractyes

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