Formability and Fatigue Behavior of Tailor (Laser) Welded Blanks for Automotive Applications
Bibliographic record
Abstract
The drive towards weight reduction in the automotive industry has led to the use of tailor welded blanks (TWBs). This work is aimed at evaluating the forming and fatigue behavior of the TWBs with different thickness combinations and compositions. Forming tests were carried out to determine the forming limit diagrams (FLDs) of the TWBs, and compared with those of the individual steel sheets. The results showed that the FLDs of the TWBs lie in-between those of the individually formed steel sheets that comprise the TWBs. A semi-empirical relation based on the mean values of the strain-hardening exponents (n-values) and of the thickness of the base metals was developed to calculate the FLDo of the TWBs. The calculated FLDo values were found to be in good agreement with the experimentally determined values. The fatigue tests showed that TWBs made from zinc coated/galvanized steels exhibited a lower fatigue limit, as compared with the TWB combinations from comparable uncoated steel. This was attributed to the intergranular cracking in the galvanized TWBs, caused by the presence of zinc penetrating beneath the sheet surface.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".