A New Approach Using EBSD to Quantitatively Distinguish Complex Transformation Products Along the HAZ in X80 Linepipe Steel
Bibliographic record
Abstract
State-of-the-art linepipe steels are microalloyed low-carbon steels that combine high strength and fracture toughness with good weldability. During welding of pipe sections the heat affected zone (HAZ) experiences rapid thermal cycles resulting in a graded microstructure that can be significantly different from that of the base metal. In particular a variety of bainitic microstructures can form in the HAZ. Depending on the type of bainite mechanical properties may be improved or may lead to poor fracture resistance and be detrimental to the overall HAZ performance. Optical microscopy is not sufficient to differentiate bainitic morphologies which vary with the transformation temperature. The investigated X80 linepipe steel also contains retained austenite at room temperature. Based on the retained austenite it is possible to characterize the orientation relationship (OR) between austenite and the transformation products. It is found that bainite shows an orientation relationship near Kurdjumov-Sachs with the prior austenite. Variant selection is related to the driving force for the bainite reaction and hence depends on the transformation temperature. In the current study Electron BackScatter Diffraction (EBSD) mapping is used to characterize transformation products based on their orientation relationship. This approach offers a quantitative way to determine volume fractions of different types of bainite in complex HAZ microstructures which is necessary to establish structure-property relationships of the HAZ.
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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".