An adapted approach for solidification crack elimination in Al7075 TIG welding
Bibliographic record
Abstract
Abstract Solidification cracking is a long-standing issue in fusion welding of high-strength aluminum alloys like Al7075, imposing limitations on their aerospace and automotive applications. The current study introduces a novel adapted approach in solidification crack elimination by incorporating TiC nanoparticles into the fusion zone using a filler paste as an easier to fabricate alternative to filler metals investigated so far. To assess the weldability of the proposed method, 3-mm thick Al7075 sheets were TIG welded (i) autogenously without any TiC nanoparticles (autogenous), (ii) heterogeneously using 1 vol.% TiC-nanoparticle enhanced Al7075 filler metal (heterogeneous filler metal), and (iii) heterogeneously using an in-house fabricated Al7075 paste containing 1 vol.% TiC nanoparticles (heterogeneous filler paste). Macroscopic analysis of weld specimens proved that both heterogeneous welding approaches effectively eliminated solidification cracks. This was confirmed by Houldcroft solidification susceptibility index deduction tests that demonstrated a strong reduction in solidification crack susceptibly in all heterogeneous joints as compared to the autogenous joint. Microstructural analysis confirmed the transformation from columnar to equiaxed grain morphology in the fusion zone as crucial factor in crack elimination. Overall, the proposed filler paste method represents a highly cost-efficient approach for eliminating solidification cracks in TIG joining of difficult to weld aluminium alloys.
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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 | 0.000 |
| 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) | 0.001 | 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".