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Record W2170991130 · doi:10.1109/tmag.2010.2091717

Topological Sensitivity Analysis for Steady State Eddy Current Problems With an Application to Nondestructive Testing

2011· article· en· W2170991130 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

VenueIEEE Transactions on Magnetics · 2011
Typearticle
Languageen
FieldEngineering
TopicNon-Destructive Testing Techniques
Canadian institutionsMcGill University
Fundersnot available
KeywordsEddy currentEddy-current testingNondestructive testingInverse problemTopology (electrical circuits)Sensitivity (control systems)Current (fluid)InverseSteady state (chemistry)Mathematical analysisComputer sciencePhysicsMathematicsGeometryElectronic engineeringEngineering

Abstract

fetched live from OpenAlex

This paper proposes a novel solution to the inverse problem of eddy current nondestructive testing (NDT) based on topological shape optimization. The topological gradient (TG) is derived for a steady state eddy current problem using a topological asymptotic expansion for the Maxwell equation of a time harmonic problem. TG provides information on where the objective function is most sensitive to topology changes and can be used as a fast identification of the locations of the defects in the test specimen. The proposed method has been applied to typical eddy current testing (ECT) problems such as buried crack reconstruction and the detection of multiple cracks. The reconstructed shape of the crack shows good agreement with the experimental data from TEAM workshop problem 15. A comparison of different ECT inverse analyses is also discussed.

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)0.000
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: Methods · Consensus signal: none
Teacher disagreement score0.289
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.049
GPT teacher head0.268
Teacher spread0.219 · 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