Asymmetrical roll bending process study : dynamic finite element modeling and experiments
Bibliographic record
Abstract
Roll bending is an efficient metal forming technique, where plates are bent to a desired curvature using forming rolls. This type of sheet forming process is one of the most widely used techniques for manufacturing axisymmetric hollow shapes. Moreover, this process is beginning to be taken into serious consideration by industries for producing large, thick parts such as the conically shaped crown of a Francis turbine runner or of a wind turbine tower. \n \nBecause of the numerous processing parameters, reducing the bending force and improving the accuracy of the final shape are significant challenges in the roll bending process. Therefore, the primary aim of this research is to find the strategies for reducing forming forces and improving final part quality by employing numerical and experimental methods. In this thesis, a 3D dynamic Finite Element (FE) model of an asymmetrical roll bending process is developed using the Ansys/LS-Dyna software. The simulation results are then compared with experiments performed with instrumented parts and roll bending machine. The parameters that affect the accuracy of the final shape, the bending forces and the residual strain left in the formed plate have been investigated. Applying this 3D dynamic FE model in an industrial context may predict the forming forces or the accuracy of the final shape’s radius and thus will decrease the setup time before manufacturing. \n \nThe forming forces can be reduced by heating the plate. In this research, the relationships between the heating plate temperature and the output parameters of roll bending process such as applied forces and final shape quality have been studied by performing FE simulation and analytical computations. These results yield to a better understanding of the mechanism of the process and provide an opportunity for the design of an efficient heating system to control the heat energy to be input in the plate during the roll bending process. \n \nThis research also proposes a new, simple approach for reducing flat areas and forming forces. This approach includes moving the bottom roll slightly along the feeding direction and adjusting the bottom roll location. The FE results indicate that this new approach effectively minimizes the flat area extents and reduces also the forming forces.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".