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Record W2326696212 · doi:10.2514/6.2012-94

Free-surface Flow Lagrangian Sensitivities

2012· article· en· W2326696212 on OpenAlex
Lise Charlot, Stéphane Étienne, Alexander Hay, Dominique Pelletier

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

Venue50th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition · 2012
Typearticle
Languageen
FieldEngineering
TopicLattice Boltzmann Simulation Studies
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsLagrangianFlow (mathematics)Surface (topology)Computer scienceMechanicsMathematicsPhysicsGeometryApplied mathematics

Abstract

fetched live from OpenAlex

A Continuous Lagrangian Sensitivity Equation Method is presented for free-surface ows. Using a front-tracking approach, the free-surface matches one of the boundaries of the computational domain and follows its deformations in time while grid motions are accounted for by an Arbitrary Lagrangian Eulerian approach. The Lagrangian sensitivity equations are derived formally by implicit total (material) di erentiation of the ow equations for shape parameters. A mapping must be used to relate the undeformed and deformed con gurations. To provide a general framework to generate this mapping for unstructured meshes and complex geometries, we use pseudo-elasticity equations. The sensitivity of free-surface boundary conditions are presented in details. Code Veri cation is performed by the Method of Manufactured Solution for the ow and their Lagrangian sensitivities. On the application side, we present the sensitivity of the location of an underwater cylinder on loads and free surface location interacting with generated swell.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
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 score0.125
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
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 head0.252
Teacher spread0.231 · 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