In situ correlative observation of humping-induced cracking in directed energy deposition of nickel-based superalloys
Why this work is in the frame
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Bibliographic record
Abstract
Directed energy deposition (DED) is a promising additive manufacturing technique for repair; however, DED is prone to surface waviness (humping) in thin-walled sections, which increases residual stresses and crack susceptibility, and lowers fatigue performance. Currently, the crack formation mechanism in DED is not well understood due to a lack of operando monitoring methods with high spatiotemporal resolution. Here, we use inline coherent imaging (ICI) to optically monitor surface topology and detect cracking in situ, coupled with synchrotron X-ray imaging for observing sub-surface crack healing and growth. For the first time, ICI was aligned off-axis (24° relative to laser), enabling integration into a DED machine with no alterations to the laser delivery optics. We achieved accurate registration laterally (<10 µm) and in depth (<3 µm) between ICI measurements and the laser beam position using a single-element MEMS scanner and a custom calibration plate. ICI surface topology is verified with corresponding radiographs (correlation >0.93), directly tracking surface roughness and waviness. We intentionally seed humping into thin-wall builds of nickel super-alloy CM247LC, locally inducing cracking in surface valleys. Crack openings as small as 7 µm were observed in situ using ICI, including sub-surface signal. By quantifying both humping and cracking, we demonstrate that ICI is a viable tool for in situ crack detection.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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