On the interplay of microstructure and residual stress in LPBF IN718
Bibliographic record
Abstract
Abstract The relationship between residual stresses and microstructure associated with a laser powder bed fusion (LPBF) IN718 alloy has been investigated on specimens produced with three different scanning strategies (unidirectional Y-scan, 90° XY-scan, and 67° Rot-scan). Synchrotron X-ray energy-dispersive diffraction (EDXRD) combined with optical profilometry was used to study residual stress (RS) distribution and distortion upon removal of the specimens from the baseplate. The microstructural characterization of both the bulk and the near-surface regions was conducted using scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD). On the top surfaces of the specimens, the highest RS values are observed in the Y-scan specimen and the lowest in the Rot-scan specimen, while the tendency is inversed on the side lateral surfaces. A considerable amount of RS remains in the specimens after their removal from the baseplate, especially in the Y- and Z-direction (short specimen dimension and building direction (BD), respectively). The distortion measured on the top surface following baseplate thinning and subsequent removal is mainly attributed to the amount of RS released in the build direction. Importantly, it is observed that the additive manufacturing microstructures challenge the use of classic theoretical models for the calculation of diffraction elastic constants (DEC) required for diffraction-based RS analysis. It is found that when the Reuß model is used for the calculation of RS for different crystal planes, as opposed to the conventionally used Kröner model, the results exhibit lower scatter. This is discussed in context of experimental measurements of DEC available in the literature for conventional and additively manufactured Ni-base alloys.
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 | 0.000 |
| 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".