Study of Deformation and Fracture of High Strength Steel Sheet during Conventional and Robust Trimming by Conducting Partial Trimming Tests
Bibliographic record
Abstract
Abstract High-strength steels are used in the automotive industry for weight reduction and improved vehicle crashworthiness. In this work, an instrumented trimming die equipped with D2 steel inserts with sharp edges was used to trim DP980 sheets with clearances of 10%, 20% and 30% of the sheet thickness. Trimming trials were conducted either without a support pad under the scrap piece (conventional trimming) or with it (robust trimming). The deformation and fracture mechanisms in the shear affected zone (SAZ) at the sheared edge of DP980 sheet specimens were investigated by performing partial trimming tests and using a new metallographic preparation method as well as 3D surface profilometry. For 10% clearance under conventional trimming, the damage distribution within the SAZ was practically symmetrical and the shearing mechanism consisted of cracks propagating simultaneously from the upper and lower surfaces of the sheet toward each other. However, the damage distribution became asymmetrical and the shearing mechanisms changed when the clearance was increased to 30%: the crack was initiated from the upper surface and propagated toward the lower surface resulting in the formation of a tensile-type burr. At 30% clearance, the robust trimming process (with a support pad) prevented the bending of the scrap piece resulting in a symmetrical damage distribution within the SAZ. In this case, a crack was initiated from the bottom surface of the sheet near the lower trim edge, and subsequently, another crack initiated from the upper surface, result in a decrease in upper die penetrations at the onset of fracture and at the end of trimming progress compare with conventional trimming. By using sharp die edge under robust trimming process, an improved sheared edge quality is achieved at larger clearances and this will help to reduce the production costs associated with dulling the die edge and the alignment of trim dies when the clearance is tight.
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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".