A new method to exploit ultrasonic vibrations in deep drawing process
Bibliographic record
Abstract
In the deep drawing process of sheet metals, lack of formability and the defects generated as a consequence of friction are two main limiting factors. Using ultrasonic vibration is an impressive way to decrease these limitations. In this paper, the ultrasonic – aided deep drawing process with a novel way of applying radial ultrasonic vibration is presented. The novelty of the presented method is using the bending mode of vibration in the sheet metal and the die using radial ultrasonic vibration. The presented method, contrary to the other techniques of applying ultrasonic vibration, has shown much fewer resonance frequency variations by changing the sheet metal geometry during the process and likewise with a variation of the clearance between the blank holder and the die. For this purpose, the finite element method was used in designing the equipment for the deep drawing process. The experimental test was done on St12 in the presence and absence of ultrasonic vibration. The effect of ultrasonic vibration in the presented method on the wrinkling and thinning defects and likewise the forming forces were experimentally studied. The results indicated the high efficiency of the presenting method in decreasing both the forming forces and the wrinkling and thinning defects. About a 42.3% decrease in the forming forces and a 4.4% decrease in the thinning effect were achieved by applying ultrasonic vibration.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".