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Record W2055795991 · doi:10.5555/2422356.2422371

Linear-time smoke animation with vortex sheet meshes

2012· article· en· W2055795991 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

VenueSymposium on Computer Animation · 2012
Typearticle
Languageen
FieldComputer Science
TopicComputer Graphics and Visualization Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPolygon meshRendering (computer graphics)Inviscid flowAnimationComputer scienceComputer graphics (images)Computational scienceAlgorithmMechanicsPhysics

Abstract

fetched live from OpenAlex

We present the first quality physics-based smoke animation method which runs in time approximately linear in the size of the rendered two-dimensional visual detail. Our fundamental representation is a closed triangle mesh surface dividing space between clear air and a uniformly smoky region, on which we compute vortex sheet dynamics to accurately solve inviscid buoyant flow. We handle arbitrary moving no-stick solid boundaries and by default handle an infinite domain. The simulation itself runs in time linear to the number of triangles thanks to the use of a well-conditioned integral equation treatment together with a Fast Multipole Method for linear-time summations, providing excellent performance. Basic zero-albedo smoke rendering, with embedded solids, is easy to implement for interactive rates, and the mesh output can also serve as an extremely compact and detailed input to more sophisticated volume rendering.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.969
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 studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
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 head0.017
GPT teacher head0.268
Teacher spread0.251 · 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