Effect of Electric Current Pulse Type on Springback, Microstructure, Texture, and Mechanical Properties During V-Bending of AA2024 Aluminum Alloy
Bibliographic record
Abstract
Abstract The present work focused on the effect of the electric current pulse type on the springback, microstructure, texture, and mechanical properties during the V-bending process of AA2024 aluminum alloy. In order to investigate this effect, three different forming conditions including conventional V-bending and electrically assisted V-bending with square and sinusoidal pulses were considered. The results indicated that the amount of springback significantly decreased from 45.5 deg (for the sample formed via conventional V-bending) to 24 deg by applying the sinusoidal pulse. Microstructural observations revealed lower stored energy in the samples formed by electric current pulses which resulted in larger grain size compared with the samples formed without electric pulses. In addition, the result showed that the intensity of the 〈111〉||BLD (bend line direction) fiber texture reduced after applying electric current pulses, whereas it was very strong in the sample formed without electric pulses. It was suggested that the electric current pulses led to change the slip plane of the dislocations from {111} to {110} through cross slip. The applying electric current pulses decrease the ultimate tensile strength (UTS) from 471.1 MPa (for the conventional tensile test) to 448.0 and 426.7 MPa for the square and sinusoidal pulses, respectively. On the other hand, the electric pulses improved the formability of the AA2024 alloy owing to the activation of more slip systems, inhibition of dislocation pinning, the promotion of dislocation movement, and the acceleration of restoration mechanisms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".