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Record W4392934792 · doi:10.1093/mnras/stae769

Hyperbolic conduction: a fast, physical conduction model implemented in smoothed particle hydrodynamics

2024· article· en· W4392934792 on OpenAlexafffund
N. A. Owens, James Wadsley

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2024
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics Simulations and Interactions
Canadian institutionsMcMaster University
FundersCompute Canada
KeywordsPhysicsSmoothed-particle hydrodynamicsThermal conductionStatistical physicsMechanicsComputational physicsClassical mechanicsAstrophysicsThermodynamics

Abstract

fetched live from OpenAlex

ABSTRACT We present the first implementation of hyperbolic thermal conduction in smoothed particle hydrodynamics. Hyperbolic conduction is a physically motivated alternative to traditional, parabolic conduction. It incorporates a relaxation time, which ensures that heat propagates no faster than a physical signal speed. This allows for larger, Courant-like, time-steps for explicit schemes. Numerical solutions of the hyperbolic conduction equations require added dissipation to remain stable at discontinuities and we present a novel scheme for this. Test cases include a simple step, the Sod Shock Tube, the Sedov–Taylor blast, and a super bubble. We demonstrate how longer relaxation times limit conduction, recovering the purely hydrodynamical results, while short relaxation times converge on the parabolic conduction result. We demonstrate that our scheme is stable with explicit Courant-like time-steps and can be orders of magnitude faster than explicit parabolic conduction, depending on the application.

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 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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.471

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 head0.011
GPT teacher head0.232
Teacher spread0.221 · 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 teacher head, 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
Published2024
Admission routes2
Has abstractyes

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