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Record W3161844816 · doi:10.1177/10775463211018306

Study on dynamics responses and applications of non-uniform beam structure under crosswind

2021· article· en· W3161844816 on OpenAlexaff
Peng Wang, Nan Wu, Haitao Luo, Zhili Sun

Bibliographic record

VenueJournal of Vibration and Control · 2021
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Vibration Analysis
Canadian institutionsUniversity of Manitoba
FundersNational Natural Science Foundation of China
KeywordsDeflection (physics)Beam (structure)VibrationMechanicsPiezoelectricityCrosswindMaterials sciencePhysicsStructural engineeringClassical mechanicsOpticsAcousticsEngineering

Abstract

fetched live from OpenAlex

This article studies the dynamic responses of the nonuniform beam structure under the action of the crosswind and its applications on vibration control and utilization (energy harvesting based on the piezoelectric beam). First, the natural frequencies and mode shapes of the nonuniform beam are solved by Adomian decomposition method and then the beam vibration deflections and piezoelectric charges are derived. Furthermore, from the theoretical model and solutions, the influences of different taper ratios and outer diameters on the deflections of nonuniform beam structures with the same mass are studied. The deflections of nonuniform same mass beam structures with positive and negative exponential profiles are also compared. It is demonstrated that the deflections of the beam decrease with the increase of taper ratios and increase with the increase of outer diameters. Under the wind velocity ranges of 10 m/s to 26 m/s, the deflection of the nonuniform beam with a negative exponent profile is less than the one with a positive exponent profile. Through this study, the optimal nonuniform beam structure with either small deflection or high piezoelectric charge output can be designed according to different wind velocities and demands.

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: Empirical
Teacher disagreement score0.340
Threshold uncertainty score0.259

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 head0.005
GPT teacher head0.237
Teacher spread0.232 · 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

Citations8
Published2021
Admission routes1
Has abstractyes

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