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Toward petascale shock/turbulence computations

2008· article· en· W2030126870 on OpenAlexfundno aff
Johan Larsson, Eric Johnsen, Sanjiva K. Lele, Parviz Moin

Bibliographic record

VenueJournal of Physics Conference Series · 2008
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaU.S. Department of Energy
KeywordsPetascale computingTurbulenceShock (circulatory)ComputationComputer scienceStatistical physicsMach numberScalingComputational fluid dynamicsReynolds numberK-epsilon turbulence modelReynolds stress equation modelK-omega turbulence modelPhysicsComputational scienceMechanicsSupercomputerParallel computingAlgorithmMathematics

Abstract

fetched live from OpenAlex

Progress toward highly resolved simulations of shock/turbulence interaction is described, with a focus on the scientific reasons for studying this problem as well as the computational issues involved. We illustrate the importance of computing shock/turbulence interaction at Reynolds numbers of at least one order of magnitude larger than previously done. We also illustrate the need to study the effect of turbulent Mach number on the interaction process. Scaling data for the code is used to estimate the computational resources needed for these novel simulations on petascale systems.

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: none
Teacher disagreement score0.592
Threshold uncertainty score0.485

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 head0.023
GPT teacher head0.214
Teacher spread0.191 · 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

Citations1
Published2008
Admission routes1
Has abstractyes

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