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Record W2137468116 · doi:10.1098/rspa.2010.0172

An acoustic analogy formulation for moving sources in uniformly moving media

2010· article· en· W2137468116 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.

Bibliographic record

VenueProceedings of the Royal Society A Mathematical Physical and Engineering Sciences · 2010
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsMcGill University
Fundersnot available
KeywordsComputationAnalogyRobustness (evolution)Fluid dynamicsAcoustic wave equationComputer scienceWave equationRest (music)Flow (mathematics)Acoustic waveMathematicsAcousticsMathematical analysisMechanicsPhysicsAlgorithm

Abstract

fetched live from OpenAlex

Acoustic analogy methods are used as post-processing tools to predict aerodynamically generated sound from numerical solutions of unsteady flow. The Ffowcs Williams–Hawkings (FW–H) equation and related formulations, such as Farassat’s Formulations 1 and 1A, are among the commonly used analogies because of their relative low computation cost and their robustness. These formulations assume the propagation of sound waves in a medium at rest. The present paper describes a surface integral formulation based on the convective wave equation, which takes into account the presence of a mean flow. The formulation was derived to be easy to implement as a numerical post-processing tool for computational fluid dynamics codes. The new formulation constitutes one possible extension of Farassat’s Formulation 1 and 1A based on the convective form of the FW–H equation.

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: Empirical
Teacher disagreement score0.335
Threshold uncertainty score0.372

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 head0.006
GPT teacher head0.211
Teacher spread0.205 · 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