Development of a Procedure for the Calculation of J-R Curves From Pressed-Notch Drop Weight Tear Test Specimens
Bibliographic record
Abstract
Over the last few years, there have been ongoing efforts funded by TransCanada PipeLines Limited to develop a more fundamentally based procedure to extract a true measure of the dynamic steady-state fracture toughness of linepipe steels. As part of this effort, considerable research has focused on the drop-weight tear test (DWTT) specimen as the baseline specimen to be used in this development. Using instrumented DWTT test equipment, dynamic load-displacement histories were extracted from the experiments. In addition, a visual measure of the crack growth, and the crack-tip-opening angle (CTOA) were obtained from high-speed video equipment. A procedure has been developed using detailed three-dimensional finite element analyses that calculate the J-integral as a function of crack growth for these dynamic experiments. The results from these analyses have been verified using published procedures on similar scale specimens. This paper presents the development of a procedure for calculating the dynamic J-R curve from the load-displacement trace of a pressed-notch DWTT specimen. The slope of the JM-R curves generated provides technical insight into the range of steady-state propagation that occurs during these experiments. The slope of the JM-R curve (dJM/da) is compared to the visually measured CTOA values and conclusions about the relationship between these parameters and the steady-state propagation energy are made. These results are key in the development of a procedure to predict steady-state fracture propagation from laboratory specimen data.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".