Dynamic distortion measurements during laser forming of Ti’6Al’4V and their comparison with a finite element model
Bibliographic record
Abstract
Laser forming is, potentially, an attractive flexible manufacturing technique for the controlled forming of aerospace alloys. Laser forming experiments using a continuous-wave CO2 laser were performed on coupons of material 80 mm × 80mm in area and 2mm thick, with sequential passes of the laser beam, at a surface scanning rate of 20 mm/s with 90 s of convective cooling between passes. A novel surface profilometer that was specifically developed to operate under the conditions of high vibration and stray light typically found in laser machining applications recorded transient surface shape changes during individual laser passes at frame rates of 4 and 0.2 Hz. A finite element model was developed using ABAQUS for the laser forming of linear bends in free Ti-6A1-4V sheets, with sequentially coupled thermal and elastic-plastic analysis incorporating temperature-dependent material properties. Transient heat source scanning was implemented to simulate the experiment. Good agreement was found between the experimental three-dimensional shape data and those predicted by the transient model. In particular, the formation of an unwanted ‘camber’ distortion perpendicular to the desired main bend was correctly predicted; its magnitude and temporal evolution throughout the three laser passes, and during the periods of convective cooling, agreed well with the experimental data. The model and the shape measurement technique will enable the future predictive controlled laser forming of more complex three-dimensional shapes.
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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 | 0.001 |
| 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 | 0.001 | 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".