Homogeneous equiaxed high-strength GH4169 components fabricated by synchronous-hot-forging-assisted laser-directed energy deposition
Bibliographic record
Abstract
• Synchronous-hot-forging-assisted promotes the formation of homogeneous equiaxed fine grains in LDED GH4169 components. • Synchronous-hot-forging-assisted enhanced the UTS and YS of GH4169 components, with the average UTS reaching a maximum value of 1175.1 MPa. • The microstructure and properties of GH4169 components were systematically investigated after synchronous-hot-forging-assisted. Laser-directed energy deposition (LDED) technology has demonstrated great potential for the rapid and integrated fabrication of nickel-based superalloy components. The plastic deformation-assisted method is crucial for achieving grain refinement and microstructural homogeneity in LDED-fabricated superalloys. However, existing methods suffer from uniformity constraints owing to their high deformation resistance, which significantly limits their application in load-bearing components. To address these issues, a synchronous-hot-forging-assisted (SHFA) LDED additive manufacturing method was proposed, and its effects on the macroscopic morphology, microstructure, and mechanical properties of GH4169 nickel-based alloy specimens were systematically compared. The results demonstrated up to 30.1% average plastic deformation in hot-forging components while maintaining good surface flatness. The synergistic effect of dislocation accumulation and dynamic recrystallization during hot forging enables dramatic grain refinement, reducing the average grain size by 89.1% (from 168.5 μm to 18.4 μm) while weakening texture intensity from 15.31 to 2.15, ultimately promoting equiaxed grain formation. The pores of hot-forging components changed from fine round to flat, the porosity decreased from 0.264% to 0.089%, and the densification level was significantly improved. With the increase in the synchronous hot-forging force, the average ultimate tensile strength of hot-forging components can reach 1175.1 MPa, while the anisotropy difference is gradually weakened. The SHFA-LDED process not only achieves excellent grain refinement and microstructure homogenization but also enhances mechanical properties, providing a new technical path for the additive manufacturing of high-performance nickel-based superalloy components.
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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".