Damage Evolution in Complex-Phase and Dual-Phase Steels during Edge Stretching
Bibliographic record
Abstract
The role of microstructural damage in controlling the edge stretchability of Complex-Phase (CP) and Dual-Phase (DP) steels was evaluated using hole tension experiments. The experiments considered a tensile specimen with a hole at the center of specimen that is either sheared (sheared edge condition) or drilled and then reamed (reamed edge condition). The damage mechanism and accumulation in the CP and DP steels were systematically characterized by interrupting the hole tension tests at different strain levels using scanning electron microscope (SEM) analysis and optical microscopy. Martensite cracking and decohesion of ferrite-martensite interfaces are the dominant nucleation mechanisms in the DP780. The primary source of void nucleation in the CP800 is nucleation at TiN particles, with secondary void formation at martensite/bainite interfaces near the failure strain. The rate of damage evolution is considerably higher for the sheared edge in contrast with the reamed edge since the shearing process alters the microstructure in the shear affected zone (SAZ) by introducing work-hardening and initial damage behind the sheared edge. The CP microstructures were shown to be less prone to shear-induced damage than the DP materials resulting in much higher sheared edge formability. Microstructural damage in the CP and DP steels was characterized to understand the interaction between microstructure, damage evolution and edge formability during edge stretching. An analytical model for void evolution and coalescence was developed and applied to predict the damage rate in these rather diverse microstructures.
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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 | 0.000 | 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) | 0.001 | 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 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".