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Record W4241145976 · doi:10.1615/ichmt.2012.cht-12.270

ADVECTION AND DIFFUSION SIMULATIONS USING LAGRANGIAN BLOCKS

2012· article· en· W4241145976 on OpenAlexaff
Vincent H. Chu, Wihel Altai

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHeat and Mass Transfer in Porous Media
Canadian institutionsMcGill University
Fundersnot available
KeywordsAdvectionComputationBlock (permutation group theory)DiffusionMoment (physics)LagrangianApplied mathematicsNumerical diffusionConvection–diffusion equationMathematicsComputer scienceMechanicsAlgorithmMathematical analysisPhysicsClassical mechanicsGeometry

Abstract

fetched live from OpenAlex

The Lagrangian block advection and diffusion is developed as an alternative numerical procedure to the solution of the transport equation. The blocks are the computational elements, which are defined by the zero, first and second moments of the blocks. The centres of mass of the blocks move with the advection velocity. The second moment of the blocks increases at a rate proportional to the diffusivity. The accuracy of the simulations by the Lagrangian block method is assessed by comparing the block simulation with an exact solution of the advection-and-diffusion equation. Unlike most numerical methods, the error associated with the Lagrangian block method is small and is not cumulative even when a very coarse block size is employed for the computation. Artificial numerical diffusion error is totally avoidable when Lagrangian blocks are used to do the computation.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.833
Threshold uncertainty score0.206

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 head0.015
GPT teacher head0.233
Teacher spread0.217 · 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
Published2012
Admission routes1
Has abstractyes

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