The Effect of Adding V and Nb Microalloy Elements on the Bake Hardening Properties of ULC Steel before and after Annealing
Bibliographic record
Abstract
Bake hardening (BH) is a vital part of special steel production. Studies in this field have focused on steels under homogeneous yielding, but until now, none have been conducted on the phenomena that occur for steels under heterogeneous yielding. In the current study, the effect of adding Nb and V alloying elements on the strength of ultra-low carbon (ULC) steel after bake hardening was investigated. The effects of pre-strain, grain size, and recrystallization annealing temperature were analyzed, as well as the effect of Nb and V on the yield stress caused by the bake hardening process. For this purpose, five types of alloys with different V and Nb contents were melted, cast in an induction furnace, and subjected to hot hammering and hot rolling. Then, cold rolling was applied to the samples by ~80%. To eliminate the effects of cold working, tensile samples were subjected to recrystallization annealing at 750 and 800 °C for 30 min, and the samples were quickly quenched in a mixture of a NaCl solution and ice. The annealed samples were subjected to a pre-tensile strain in the range of 2-12% and then aged in a silicone oil bath at 180 °C for 30 min. Then they were subjected to a tensile test. The obtained results showed that with the increase of the pre-strain and the annealing temperature, the values of baking hardness increased. The presence of V in the composition of steel reduced the annealing temperature.
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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 | 0.001 | 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".