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Record W4394880922 · doi:10.1007/s10665-024-10357-z

Implicit interpolation method for immersed boundary methods

2024· article· en· W4394880922 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

VenueJournal of Engineering Mathematics · 2024
Typearticle
Languageen
FieldEngineering
TopicLattice Boltzmann Simulation Studies
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsInterpolation (computer graphics)Boundary (topology)MathematicsImmersed boundary methodMathematical analysisBoundary value problemBilinear interpolationBackward Euler methodDomain (mathematical analysis)Boundary conditions in CFDApplied mathematicsLinear interpolationStencilTrilinear interpolationEuler equationsRobin boundary conditionMixed boundary conditionComputer scienceComputational scienceMotion (physics)

Abstract

fetched live from OpenAlex

Abstract Immersed boundary (IB) methods have been successfully implemented for different applications. This paper focuses on the immersed boundary implementation for two different governing equations, namely the diffusion equation and Euler equations, using a bi-linear interpolation for the implementation of the boundary condition. The concept of implicit interpolation is introduced which eradicates the problems faced with the explicit interpolation in which it is required to move away from the boundary in the fluid domain in order to complete the interpolation stencil.

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 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 score0.204
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.028
GPT teacher head0.362
Teacher spread0.335 · 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