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Record W4402071936 · doi:10.58286/30188

Theory of similarity and ultrasonic testing

2024· article· en· W4402071936 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

Venuee-Journal of Nondestructive Testing · 2024
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsKinectrics (Canada)
Fundersnot available
KeywordsCorrosionReinforced concreteForensic engineeringMaterials scienceEngineeringStructural engineeringMetallurgy

Abstract

fetched live from OpenAlex

Application of similarity theory (dimensional analysis) to ultrasonic (UT) testing is discussed using as an illustration the example of concrete blocks. The concept of dimensional analysis makes it possible to represent a physical system via a minimal set of variables, the so-called π groups, which are the dimensionless quantities. These dimensionless parameters, characterizing the respective phenomenon, should have approximately equal values for the real object and for the model. Small concrete samples have been tested in the lab conditions using various UT probes and techniques. Two dimensionless criteria, valid and similar for the real field case and for the laboratory samples, have been introduced: total attenuations of UT waves and ratios of void size to the UT wavelength. To get total attenuations in the field conditions for thick concrete block, similar to the total attenuations measured in lab experiments on small samples, one should apply the low-frequency UT waves 60-100kHz. However, these UT waves will be able to reliably detect only the large inhomogeneities (e.g. voids), whose size is about half of the used UT wave, i.e. inhomogeneities with dimensions larger than 20-40mm.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.542
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 head0.034
GPT teacher head0.246
Teacher spread0.212 · 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