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Record W2324736649 · doi:10.2514/6.2015-3198

Opportunities for efficient high-order methods based on the summation-by-parts property (Invited)

2015· article· en· W2324736649 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venue22nd AIAA Computational Fluid Dynamics Conference · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced Numerical Methods in Computational Mathematics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsProperty (philosophy)Computer scienceOrder (exchange)EpistemologyBusinessPhilosophy

Abstract

fetched live from OpenAlex

Summation-by-parts (SBP) operators are traditionally viewed as high-order finite-difference operators, but they can also be interpreted as finite-element operators with an implicit basis. Such an element-based perspective leads to several opportunities that we describe. The first is provided by generalized one-dimensional SBP operators, which maintain the desirable properties of classical SBP operators while permitting flexible nodal distributions. The second opportunity is to extend the SBP definition to multiple dimensions, and a recently proposed definition for multidimensional SBP operators paves the way for time-stable, high-order finite-difference operators on unstructured grids. The final opportunity that we discuss is an analogy with the continuous Galerkin finite-element method, which leads to a systematic means of assembling SBP operators on a global domain from elemental operators. To illustrate these ideas, high-order SBP operators are constructed for the triangle and tetrahedron, and the former are assembled into a global SBP operator and applied to a linear convection problem on a triangular grid.

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.

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)0.001
metaresearch head score (Gemma)0.001
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: Methods · Consensus signal: Methods
Teacher disagreement score0.243
Threshold uncertainty score0.867

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.109
GPT teacher head0.325
Teacher spread0.216 · 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