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Record W7133078531

Ultrasonic nondestructive evaluation of cylindrical components by resonance acoustic spectroscopy

2002· dissertation· W7133078531 on OpenAlexfundno aff
Ying Fan

Bibliographic record

VenueTSpace · 2002
Typedissertation
Language
FieldEngineering
TopicUltrasonics and Acoustic Wave Propagation
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTransverse isotropyRodCylinderIsotropyIsotropic solidNondestructive testingAcoustic resonanceUltrasonic sensorPlane (geometry)
DOInot available

Abstract

fetched live from OpenAlex

Potential applications of Resonance Acoustic Spectroscopy (RAS) for the purpose of Nondestructive Evaluation (NDE) of isotropic clad rods and transversely isotropic cylinders encased in a solid elastic medium are investigated in this thesis. Mathematical models are developed for: (1) scattering of an obliquely incident plane acoustic wave from a transversely isotropic cylinder encased in a solid isotropic matrix and (2) scattering of a normally incident plane acoustic wave from an immersed isotropic clad rod with imperfect adhesion between the core and cladding. In these mathematical models, the scattered pressure field is obtained using a normal-mode expansion method. Experimental measurements of the scattered pressure fields are carried out using the short-pulse Method of Isolation and Identification of Resonances (MIIR). The method is applied to: copper-clad aluminum rods made from explosive welding and fiber-reinforced composite rods embedded in a solid medium. The experimental results show good agreement with the results obtained from the mathematical models. It is concluded that RAS has potential applications for nondestructive evaluation of various cylindrical components.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.302
Teacher spread0.279 · 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 designBench or experimental
Domainnot available
GenreMethods

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
Published2002
Admission routes1
Has abstractyes

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