Analytical Modeling and FE Simulation for Analyzing Applied Forces During Roll Bending Process
Bibliographic record
Abstract
High strength steel is widely used in the manufacturing of parts dealing with heavy cyclic loads and corrosive environments. However, processing this type of steel is not easy, and it becomes a hard-to-solve problem when the part to produce is large, thick and quasi-unique. One example of a thick high strength steel axisymmetric part is the conical shape of the crown of a Francis turbine runner. Some Francis turbine runners installed in the dam basement of a hydraulic power plant are 10 meters in diameter with more than 5 meters in height, while plate thickness can exceed 100 millimeters. Several processes can be envisaged for the manufacturing processes of such large parts (welding or casting…), but few processes can deliver one within a reasonable time and at competitive cost. Among them the roll bending process, causing plastic deformation of a plate around a linear axis with little or no change in plate thickness, is considered as an interesting alternative. The main objective of this research is to assess 3D dynamic finite element and analytical models for the computation of the bending forces during the manufacturing of hollow conical parts made of a thick plate and a high strength steel. Numerous parameters such as thickness, curvature, part size, material properties and friction directly influence the reaction forces on the rolls. Therefore, the results of this research provide a better understanding of the phenomena taking place in the process, and an opportunity to establish relationships between the bending forces and the parameters of a final conical part.
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 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 | 0.000 |
| 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) | 0.000 | 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".