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Record W2235731660

A level set method without re-initialization

2012· article· en· W2235731660 on OpenAlex

Why this work is in the frame

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affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Numerical Methods in Computational Mathematics
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsInitializationLevel set methodLevel set (data structures)Volume of fluid methodFinite element methodSet (abstract data type)Computer scienceApplied mathematicsAlgorithmDomain (mathematical analysis)Interface (matter)Scale (ratio)MathematicsMathematical optimizationFlow (mathematics)Mathematical analysisImage (mathematics)Artificial intelligenceGeometryImage segmentationPhysicsBubble
DOInot available

Abstract

fetched live from OpenAlex

Moving interface problems have practical applications in the fields of fluid mechanics, solid mechanics or medical imaging. There are several numerical methods in CFD to solve these problems. The volume of fluid method (VOF) of Hirt and Nichols set in 1981 is widely used for cases where the interface separates the domain into two distinct areas as in the case of two-phase flows [1]. The mixture model is based on the principle of averaged equations. The method of averaging is a wise choice to do [2] when the scale of one of the phases is too small compared to the others [3, 4]. The Level set method was first introduced by Osher and Sethian [5] to capture a moving front. This method was originally developed for the simulation of a phase change problem governed by a diffusion equation. Other applications followed in image analysis [6]. Earlier, the Level set equation was solved with the method of finite differences. Recently, a new variational formulation has been developed in order to remove the re-initialization process which is a reset phase [7]. Moreover, in most cases we are interested in having greater accuracy at the interface and not in the entire domain. Hence, the Level set method restricted to a narrow band around the zero level set was developed [8]. In this paper, a new stabilized finite element formulation is introduced to solve the level set equation without re-initialization. This method is compared with the one introduced in [7] on a timereversed flow field case [10]. 1. THE LEVEL SET METHOD The Level set method was introduced in 1988 by Osher and Sethian [5]. The starting point of this method is the definition of a level set scalar function . The zero value of the level set function is the interface that is transported by the velocity field. The contours of the level set function initialized as a distance function may move away from the level set distance function due to the accumulation of numerical errors, hence the need to reset the solution after a number of steps. The moving interface is the zero-level for the scalar function ( ): ( ) { ( ) }. For example in a two-phase flow the domain is divided into two subdomains using the sign of the level set function:

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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: Methods · Consensus signal: Methods
Teacher disagreement score0.253
Threshold uncertainty score0.352

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 head0.168
GPT teacher head0.417
Teacher spread0.249 · 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