IMPROVING THE FORMABILITY OF STAINLESS STEEL 321 THROUGH MULTISTEP DEFORMATION FOR HYDROFORMING APPLICATIONS
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Tube hydroforming (THF) is a well established process in the automotive industry and its application is being extended to the aerospace for manufacturing complex geometries. However, most of the alloys used in aerospace are high in strength and low in formability, which renders the application of THF more challenging. The objective of this paper is to present a method to increase the formability of an austenitic stainless steel. A multistep forming process was simulated through interrupted uniaxial tensile testing experiments to study the influence of the latter process on formability. The tensile test was divided into several deformation steps with a stress relief heat treatment after each forming step. The results indicated that the application of intermediate heat treatments considerably increased the formability of the stainless steel 321 alloy (SS321). Microstructure evolution as a function of deformation or heat treatment parameters was also investigated and revealed the formation of strain-induced martensite after the first deformation and heat treatment cycle without any deleterious effect on formability enhancement.
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.
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 | 0.001 |
| 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 it