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Record W4205820070 · doi:10.22215/etd/2021-14645

Dynamic Aeroelastic Response Attenuation of Aerospace Structures Employing Passive Tuned Mass Dampers

2021· dissertation· en· W4205820070 on OpenAlexaff
Victor E. L. Gasparetto

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicVibration Control and Rheological Fluids
Canadian institutionsCarleton University
Fundersnot available
KeywordsAeroelasticityTuned mass damperStructural engineeringStiffnessEngineeringTrussDisplacement (psychology)Control theory (sociology)DamperAttenuationMinificationComputer scienceAerodynamicsAerospace engineeringPhysics

Abstract

fetched live from OpenAlex

This thesis proposes an optimization procedure to achieve the best configuration of Multiple Degrees of Freedom (MDOF) tuned mass dampers (TMD) to mitigate the global dynamic aeroelastic response of aerospace structures. The TMD design parameters are investigated in terms of their individual mass, stiffness, damping, and location on the target structure. In order to determine the optimum sets of TMD, a Multi-Objective design optimization employing Genetic Algorithm (MOGA) is implemented, where the selected fitness functions for the analysis are the minimization of the total mass included with the resonators and concurrent minimization of the peak displacement at a specific structural nodes in space.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.667
Threshold uncertainty score1.000

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)0.0010.000

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 head0.006
GPT teacher head0.228
Teacher spread0.222 · 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.

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

Citations0
Published2021
Admission routes1
Has abstractyes

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