Reliability Analysis of the Tube Hydroforming Process Based on Forming Limit Diagram
Bibliographic record
Abstract
Tube hydroforming has become an increasingly attractive manufacturing process in automotive industry due to it having several advantages over alternative methods. The forming limit diagram has been extensively used in metal forming as the criteria of formability. A method to assess the probability of failure of the process based on reliability theory and the forming limit diagram is proposed in this paper. The tube hydroforming process is affected by many parameters such as geometry, material properties, and process conditions. Finite element simulation was used to predict the relationship between the strain and these parameters, and a numerical method was applied to get the statistical distribution of the strain. Based on the forming limit band in the forming limit diagram, the reliability of the forming process can be evaluated. A tube hydroforming process of free bulging is then introduced as an example to illustrate the approach. The results show this reliability evaluation technique to be an innovative approach for product designers and process engineers to avoid failure during tube hydroforming.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".