Numerical Modeling of Tube Hydropiercing Using Phenomenological and Micro-Mechanical Damage Criteria
Bibliographic record
Abstract
Hydropiercing is an efficient way of piercing holes in mass produced hydroformed parts with complex geometries. By driving piercing punches radially into a hydroformed and fully pressurized tube, holes will be pierced and extruded into the tube-wall. Recent experimental studies have shown that the formability of advanced high strength steel (AHSS) tubes can be increased with the application of internal pressure. In this study, three-dimensional finite element simulations of a tube hydropiercing process of a dual phase steel (DP600) were performed in LS-DYNA, using phenomenological, micromechanical and combined damage criteria. Damage was included in the numerical analysis by applying constant equivalent plastic strain (CEPS), the Gurson-Tvergaard-Needleman (GTN), and the Extended GTN (GTN+JC) model. In order to calibrate the parameters in each model, a specialized hole-piercing fixture was designed and piercing tests were carried out on non-pressurized tube specimens. Of the various ductile fracture criteria, the results predicted with the GTN+JC model, such as the punch load-displacement, the roll-over depth, and the quality of the clearance zone correlated the best with the experimental data.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".