MétaCan
Menu
Back to cohort
Record W3198980937 · doi:10.17762/de.vi.4301

Free Vibration Analysis of Hybrid And Non-Hybrid GFRP Composite Wind Turbine Blade

2021· article· en· W3198980937 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueDesign Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicVibration and Dynamic Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsFibre-reinforced plasticTurbine bladeVibrationStructural engineeringBlade (archaeology)Composite numberWind powerStiffnessMaterials scienceRenewable energyTurbineGlass fiberComposite materialMechanical engineeringEngineeringAcoustics

Abstract

fetched live from OpenAlex

Wind energy is one prominent solution to mitigate the increasing energy demand. Composite materials are exhibiting enormous advantages with their tailor-made properties. With the development of renewable energy power generation, the issue of blade vibration reduction has gotten a lot of technical attention. It has become an essential technique for blade analysis and design. Various attempts were recorded to reduce the vibration of the blade and enhance its natural frequencies. The present work aimed to characterize the mechanical properties of the GFRP composite material and the GFRP composite with 4wt% of the MWCNT filler. Both hybrid and non-hybrid GFRP are subjected to characterization, with the same free vibration analysis of NACA 63-415 wind turbine blades being analyzed. The study results revealed that the hybrid GFRP has more stiffness, which causes it to enhance the free vibrations in all mode shapes.

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: none
Teacher disagreement score0.801
Threshold uncertainty score0.802

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.006
GPT teacher head0.181
Teacher spread0.175 · 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