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Record W2801132170 · doi:10.1139/tcsme-2016-0071

RESEARCH ON THE SELF-SYNCHRONOUS VIBRATION OF FATIGUE LOADING TESTS FOR WIND TURBINE BLADES

2016· article· en· W2801132170 on OpenAlexvenueno aff
Leian Zhang, Wei Xiuting

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicVibration and Dynamic Analysis
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsVibrationBlade (archaeology)Structural engineeringTurbine bladeNatural frequencyControl theory (sociology)TurbineEngineeringComputer scienceMechanical engineeringAcousticsPhysicsControl (management)

Abstract

fetched live from OpenAlex

To carry on fatigue loading tests for wind turbine blades accurately, the self-synchronous vibration mechanism of loading system was investigated. Firstly, the mathematical model of vibration was deduced based on LaGrange Equation, thus the influence factors of self-synchronous vibration could be obtained. Then to study the influencing rules of the initial phase difference between loading equipment and blade, a simulating model was constructed to carry on the numerical simulation and it was found that when the driving frequency of the loading equipment was the same as the natural frequency of the blade, a different initial phase separation would generate different effect on self-synchronous vibration. Finally, an on-site fatigue test system was established to verify the accuracy of mathematical and simulation model mentioned above. It could be concluded that the test results were consistent with the simulating result. The research on the self-synchronous vibration performance of loading system for blade could supply a theory support for the sequent control of blade’s fatigue tests precisely.

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 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 score0.987
Threshold uncertainty score0.277

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 head0.030
GPT teacher head0.260
Teacher spread0.230 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations1
Published2016
Admission routes1
Has abstractyes

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