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Record W4385403800 · doi:10.1016/j.simpa.2023.100557

Hyper2D: A finite-volume solver for hyperbolic equations and non-equilibrium flows

2023· article· en· W4385403800 on OpenAlexafffund
Stefano Boccelli

Bibliographic record

VenueSoftware Impacts · 2023
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaPolitecnico di MilanoUniversity of OttawaNvidia
KeywordsFortranSolverPartial differential equationFinite volume methodApplied mathematicsHyperbolic partial differential equationComputer scienceOrdinary differential equationCUDAComputational scienceMathematicsDifferential equationPhysicsMathematical optimizationMathematical analysisMechanicsParallel computing

Abstract

fetched live from OpenAlex

Hyper2D is a finite-volume solver for hyperbolic partial differential equations (PDEs) and non-equilibrium flows. Its minimalistic structure makes Hyper2D quickly adaptable to one's needs. Non-standard systems of equations and source terms are easily implemented by modifying a single pde file. In our research, we use Hyper2D for studying rarefied hypersonic gas dynamic problems (moment methods), relativistic flows, multi-fluid plasma models and kinetic theory (1D1V Boltzmann/BGK equation). The package includes (i) a one-dimension Octave/MATLAB version, aimed at familiarizing with the method, (ii) a single-core Fortran version, with higher-order accuracy in space and time, and (iii) a CUDA Fortran version.

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)0.001
metaresearch head score (Gemma)0.003
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: Software · Consensus signal: none
Teacher disagreement score0.038
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0380.007

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 head0.012
GPT teacher head0.232
Teacher spread0.220 · 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
GenreSoftware

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

Citations3
Published2023
Admission routes2
Has abstractyes

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