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Record W2805525611 · doi:10.1139/cjce-2017-0010

Identification of aerodynamic derivatives of bridge decks at high testing wind speed

2018· article· en· W2805525611 on OpenAlexvenueno aff
Quanshun Ding, Shuanghu Dong, Zhiyong Zhou

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Vibration Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsAerodynamicsStructural engineeringWind speedFlutterWind tunnelModalAeroelasticityVibrationDeckBridge (graph theory)EngineeringAerodynamic forceReliability (semiconductor)AcousticsAerospace engineeringMaterials sciencePhysicsPower (physics)Meteorology

Abstract

fetched live from OpenAlex

An identification of eight aerodynamic derivatives based on dual-mode and single-mode extraction of system is presented to improve the applicability and accuracy of identification at high testing wind speed. The participation rate to measure the contribution of modes on free-vibration responses is defined and the single-mode extraction is presented to extract the modal parameters of the system at high wind speed. To verify the reliability and applicability of the presented method, the aerodynamic derivatives of a dummy section with known self-excited forces are identified. It is noted that there is a very good agreement between the identified results and the target ones in the range of the low and high wind speeds and the presented method works well after the critical state of flutter. The sectional wind tunnel test of the Tanggu-haihe bridge is performed to identify the aerodynamic derivatives of the deck at the attack angles of −3°, 0°, and 3°.

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 score0.261
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.009
GPT teacher head0.193
Teacher spread0.183 · 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
Published2018
Admission routes1
Has abstractyes

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