Aspects of Weld Metallurgical Characteristics and Fracture Mechanism in Formability Tests of Non-Vacuum Electron Beam Tailor-Welded AA5754-O temper Aluminum Blanks
Bibliographic record
Abstract
This study determines the correlation between microstructure, fracture mechanism and formability of Al tailor-welded blanks (TWBs). It is found that porosity in the welds is detrimental to the formability of non-vacuum electron beam (NVEB) welded AA5754-O temper Al TWBs. It is also found that the degree of influence of the weld characteristics on formability can be minimal in one test condition, but critical in another, depending on the loading condition, strain state (related to blank geometry) and relative position of the weld seam to the major strain during forming. Metallography, microhardness measurement, electron probe chemical analysis and fractography for 1-2 mm NVEB AA5754-O temper of Al TWBs were used to analyze precipitation, porosity, grain structure, microhardness profile and microchemistry profile across the weld of Al TWBs and their fracture mechanisms during forming tests. Formability of the NVEB welded AA5754 Al TWBs has been previously evaluated. In this study, observations of the failure location are carried out on those specimens subjected to transverse tensile, longitudinal tensile, transverse dome and longitudinal dome tests.
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 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".