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Record W4313456243

Multidimensional aware Riemann solver for the Eulerian droplet equation system

2022· preprint· en· W4313456243 on OpenAlexaff
Héloïse Beaugendre, Agnes Chan, Gérard Gallice, Raphaël Loubère, Pierre‐Henri Maire, François Morency, Thomas Vigier

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2022
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicAquatic and Environmental Studies
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsRiemann solverEulerian pathSolverRiemann problemComputer scienceRiemann hypothesisApplied mathematicsMathematicsMathematical analysisPhysicsMechanicsProgramming languageLagrangian
DOInot available

Abstract

fetched live from OpenAlex

In clouds and under cold weather, water droplets impact and freeze on aircraft struc-tures. The Eulerian model for the air-droplet flow predicts the droplet impingement. The model equations are close to the Euler equations but without a pressure term. Consequently, the resulting system is weakly hyperbolic and standard Riemann solvers cannot be used. To circumvent this problem, the system is modified to include the divergence of a particle pressure. The main purpose of this work is to implement a multidimensional HLLC Riemann solver for the modified formulation of the Eulerian droplet model. The method should preserve physical properties such as the density positivity and must produce accurate results compared to existing codes.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.205
Teacher spread0.183 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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