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Record W112479126 · doi:10.5006/c2001-01074

Understanding the Size Effect in Nace TM0177 Method D (DCB) Testing and Implications for Users

2001· article· en· W112479126 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIndustrial Vision Systems and Defect Detection
Canadian institutionsShell (Canada)
Fundersnot available
KeywordsMaterials scienceComputer science

Abstract

fetched live from OpenAlex

Abstract The double cantilever beam (DCB) test is being increasingly used in the process of qualifying materials for sour service. Although the DCB test has been standardized in NACE Standard TM0177, Method D, it is acknowledged that variables such as specimen geometry, test temperature and initial loading can affect KISSC values even when they remain within the tolerances of the test method. This can make it challenging to set uniform acceptance/rejection criteria. Understanding the behaviour of subsize DCBs is particularly important because many components in sour service can only be tested using subsize DCBs. The present work shows that specimen geometry, test temperature and loading conditions are all related. An empirical specimen thickness and test temperature correlation is given for an API 5CT T95 material. An explanation for the observed behaviour for carbon and low alloy steels is given and implications for both performers of the test method and end users of the tested components are discussed. Potential changes to the NACE International TM0177 Method D test are considered.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.778
Threshold uncertainty score0.226

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.136
GPT teacher head0.325
Teacher spread0.189 · 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