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Record W2624019580

Innovative Model for Flow Governed Solid Motion based on Penalization and Aerodynamic Forces and Moments

2015· preprint· en· W2624019580 on OpenAlexaff
Héloïse Beaugendre, François Morency

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2015
Typepreprint
Languageen
FieldEngineering
TopicLattice Boltzmann Simulation Studies
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsAerodynamicsAerodynamic forceFlow (mathematics)MechanicsMotion (physics)Moment (physics)Statistical physicsPhysicsMathematicsComputer scienceClassical mechanics
DOInot available

Abstract

fetched live from OpenAlex

This work proposes a fluid-solid interaction model. It is formulated for a laminar flow modeled by the incompressible Navier-Stokes equations in which we consider the presence of a rigid moving solid. The model is formulated inside an immersed boundary method based on a penalization technique. The penalization technique imposes the body effects on the flow. The velocity field is extended inside the solid region and a penalty term enforces the rigid motion inside the solid region. This technique offers a great flexibility to modify the geometry of the solid. The forces and angular momentum needed for the fluid-solid interaction model are computed with an innovative method suitable for the penalized equations method. The method is validated successfully for an oscillating airfoil in large flapping motion. Effects of different geometries on aerodynamic coefficients can then be explored. The fluid-solid interaction model is also verified for solid motions governed by the flow, such as falling cylinder and plate.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.844
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.022
GPT teacher head0.250
Teacher spread0.229 · 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.

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

Citations2
Published2015
Admission routes1
Has abstractyes

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