Influence of Specimen Size on the SCC Growth Rate of Ni-Alloys Exposed to High Temperature Water
Bibliographic record
Abstract
Abstract Tests were conducted on a single heat of Alloy 600 using compact tension specimens ranging from 50.80 mm (2 inches) in gross thickness (2T) to 10.16 mm (0.4 inches, 0.4T) in gross thickness. Results indicated that at stress intensity factor (K) levels above 55 MPa√m, the growth rate is affected by specimen size in deaerated primary water. The growth rate can be significantly faster in 0.4T and 0.6T (15.24 mm = 0.6 inches in gross thickness) specimens at these elevated K levels compared to 2T specimens. Stress corrosion crack (SCC) growth rates > 6 x 10-7 mm/s were observed at 338°C and 40 cc/kg H2 in 0.6T and 0.4T specimens at these elevated K levels, although the fracture mode was not significantly affected by the specimen size. The SCC growth rate of 2T specimens under comparable test conditions was ~6 x 10-8 mm/s. All of the specimens examined that were tested at K > 55 MPa√m exhibited intergranular failure, although ductile dimples and cracked grains were observed in the 0.4T specimens loaded to the elevated K levels. The effect of specimen size on the crack growth behavior indicated by electric potential drop (EPD) monitoring at K > 55 MPa√m was also reviewed. EPD indicated steady state crack growth during the tests conducted on 1T (25.4 mm = 1.0 inches in gross thickness) and 2T specimens. Steady state crack growth was not indicated by EPD for the 0.4T and 0.6T specimens loaded at K > 55 MPa√m. EPD indicated large jumps in the crack length at discrete points. Initially, it was believed that these large, rapid increases in the crack length corresponded to ductile tearing of uncracked ligaments in the crack wake as the SCC crack advanced. However, examination of the fracture surfaces did not reveal any evidence of isolated regions of ductile tearing in the crack wake. The large increases in the EPD signal were due to strain bursts. These results highlight the need to base SCC growth rates on destructive examination of the specimen.
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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".