Understanding the Size Effect in Nace TM0177 Method D (DCB) Testing and Implications for Users
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".