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Record W4328028319 · doi:10.1111/cgf.14625

Surface‐Only Dynamic Deformables using a Boundary Element Method

2022· article· en· W4328028319 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

VenueComputer Graphics Forum · 2022
Typearticle
Languageen
FieldEngineering
Topic3D Shape Modeling and Analysis
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBoundary element methodComputer scienceAnimationSimple (philosophy)Linear elasticitySurface (topology)Elasticity (physics)Constraint (computer-aided design)Element (criminal law)Displacement (psychology)Boundary (topology)AlgorithmFinite element methodComputer graphics (images)GeometryMathematicsStructural engineeringMathematical analysisPhysics

Abstract

fetched live from OpenAlex

Abstract We propose a novel surface‐only method for simulating dynamic deformables without the need for volumetric meshing or volumetric integral evaluations. While based upon a boundary element method (BEM)for linear elastodynamics, our method goes beyond simple adoption of BEM by addressing several of its key limitations. We alleviate large displacement artifacts due to linear elasticity by extending BEM with a moving reference frame and surface‐only fictitious forces, so that it only needs to handle deformations. To reduce memory and computational costs, we present a simple and practical method to compress the series of dense matrices required to simulate propagation of elastic waves over time. Furthermore, we explore a constraint enforcement mechanism and demonstrate the applicability of our method to general computer animation problems, such as frictional contact.

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: none
Teacher disagreement score0.743
Threshold uncertainty score0.835

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.013
GPT teacher head0.250
Teacher spread0.237 · 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