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Record W2065343416 · doi:10.1784/insi.46.7.396.55583

In-service corrosion evaluation in pipelines using gamma radiography – a numerical approach

2004· article· en· W2065343416 on OpenAlexaff
Kaveh Edalati, N. Rastkhah, A. Kermani, M. Seiedi, Amir Movafeghi

Bibliographic record

VenueInsight - Non-Destructive Testing and Condition Monitoring · 2004
Typearticle
Languageen
FieldEngineering
TopicNon-Destructive Testing Techniques
Canadian institutions123 Certification (Canada)
FundersInternational Atomic Energy Agency
KeywordsCorrosionPipeline transportService (business)Forensic engineeringRadiographyNuclear engineeringEnvironmental scienceMaterials scienceEngineeringMetallurgyBusinessMedicineRadiologyEnvironmental engineering

Abstract

fetched live from OpenAlex

Wall thickness measurement and deterioration determination of 6 and 10 inch pipes due to corrosion/erosion/pitting was evaluated by using radiographic film density measurements. Special reference blocks were prepared withdefined step wall reductions and artificial defects. Gamma radiography with a Ir-192 source was used. A double-wall technique with longitudinal film arrangement was used for this purpose. Formulae were developed from the experiments for numerical calculations. It was observed that this method can determine remaining wall thickness as well as pitting corrosion in insulated and non-insulated pipes with differential and absolute density measurements. The purpose of the work was the optimisation of techniques, quality control, evaluation of radiographs and parameters affecting the results. Furthermore, the studies included investigation on the limitations of each technique and stability of test conditions. Results show good precision - above 97% - between real and calculated values.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.043
GPT teacher head0.288
Teacher spread0.245 · 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

Citations8
Published2004
Admission routes1
Has abstractyes

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