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Record W2078778560 · doi:10.1109/tmtt.2010.2040343

Towards the Development of an Unconditionally Stable Time-Domain Meshless Method

2010· article· en· W2078778560 on OpenAlexaff
Yiqiang Yu, Zhizhang Chen

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2010
Typearticle
Languageen
FieldEngineering
TopicNumerical methods in engineering
Canadian institutionsDalhousie University
Fundersnot available
KeywordsInterpolation (computer graphics)Regularized meshless methodStability (learning theory)Applied mathematicsMeshfree methodsComputer sciencePoint (geometry)Domain (mathematical analysis)Mathematical optimizationSingular boundary methodAlgorithmMathematicsMathematical analysisFinite element methodArtificial intelligencePhysicsGeometry

Abstract

fetched live from OpenAlex

In this paper, an unconditionally stable mesheless method is proposed with the implementation of the leapfrog alternating-direction-implicit scheme in the 3-D radial point interpolation meshless method. The unconditional stability of the proposed method is analytically proven and numerically verified. The accuracy and efficiency of the method are assessed through experiments. Compared with the conventional radial interpolation method, the computational cost can be saved by 85% with little sacrifice of accuracy. The principle presented in this paper can be extended to other existing meshless methods in developing other types of the unconditionally stable meshless methods.

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.010
GPT teacher head0.267
Teacher spread0.257 · 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
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

Citations75
Published2010
Admission routes1
Has abstractyes

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