Study of True Stress-Strain Curve after Necking for Application in Ductile Fracture Criteria in Tube Hydroforming of Aerospace Material
Bibliographic record
Abstract
Tube hydroforming (THF) is an advanced metal forming process that is used widely in automotive industry, but the application of the THF process in aerospace field is comparatively new with many challenges due to high strength and limited formability of aerospace materials. The success of THF process largely depends on many factors, such as mechanical properties of the material, loading path during the process, tool geometry and friction condition. Due to complexity of this process, finite element modeling (FEM) can largely reduce the production cost. One of the important input in FEM is the material behavior during hydroforming process. The true stress-strain curve before necking can be easily determined, using either tensile testing or bulge testing, but for an accurate failure prediction in a large deformation, such as hydroforming, the study of true stress-strain curve after necking is important because it improves the quality of the analysis due to utilizing a real extended stress-strain curve. Hence, the objective of this research was to establish a methodology to determine the true stress-strain curve after necking in order to predict burst pressure in the THF of aerospace materials. Uniaxial tensile tests were performed on standard tensile samples (ASME E8M-04) to determine the true stress-strain before and after necking, using an analytical method presented in this study. To validate the approach, burst pressure in the THF process was predicted using the extended stress-strain curve in conjunction with Brozzo's decoupled fracture model. The approach was evaluated using data obtained from the free expansion (tube bulging) tests performed on stainless steel 321 tubes with 2 inches diameter and two different thicknesses, 0.9 mm and 1.2 mm. The comparison of the predicted and measured burst pressures was promising, indicating that the approach has the potential to be extended to predict formability limits in THF of complex shapes.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".