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Record W2135430997 · doi:10.1109/tim.2010.2047149

Long-Duration Time-Resolved PIV to Study Unsteady Aerodynamics

2010· article· en· W2135430997 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueIEEE Transactions on Instrumentation and Measurement · 2010
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsWestern University
Fundersnot available
KeywordsAerodynamicsParticle image velocimetryFlutterBluffInstabilityWakeTurbulenceMechanicsFlow (mathematics)Aerospace engineeringPhysicsEngineering

Abstract

fetched live from OpenAlex

A time-resolved particle image velocimetry (PIV) system has been developed at the University of Western Ontario, London, ON, Canada, with long-recording-time capabilities. This system is uniquely suited to the study of unsteady aerodynamics and hydrodynamics, such as avian aerodynamics or bluff-body oscillations. Measurements have been made on an elongated bluff body through the initial build-up phase of flutter. The possibilities to study this instability, which was responsible for the collapse of the Tacoma Narrows Bridge, are significantly broadened by the use of this system. The long-time recording capability of the system allows for novel results since it yields data that are spatially and temporally resolved over a long record length. The buildup of flutter is shown to exhibit complex dynamics that are heavily influenced by the flow-induced motion of the body. Features of the wake turbulence as a function of time are presented and shown to substantially vary.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.583
Threshold uncertainty score0.770

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 head0.014
GPT teacher head0.221
Teacher spread0.207 · 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