Residual stress prediction in machining of parts fabricated by directed energy deposition
Bibliographic record
Abstract
The residual stress exhibited in post-machined metallic components fabricated by directed energy deposition (DED) determines their final mechanical performance and reliability in mission-critical applications. This study develops a numerical model to predict the final surface residual stress after the orthogonal cutting of DED-produced IN718, which integrates two critical factors: DED-induced initial residual stress states and microstructure properties. Using the developed modeling procedure, the penetration depth of post-machining into the initial residual stress distribution can be effectively quantified, which aligns with residual stress measurements through X-ray diffraction. The developed model is further employed to quantify the cumulative effects of initial residual stress states and grain size on cutting forces and final surface residual stress profiles. The results suggest that, under the given orthogonal cutting conditions of DED parts, variations in the initial residual stress states of the chip formation region have negligible effects on cutting forces. However, magnitudes of surface compressive residual stress in the longitudinal direction reduce by 21.8 %-52.3 % as the initial residual stress states shift from compressive-dominant to tensile-dominant, and decrease by 23.8 %-54.0 % as the built-in grain size ( d g _ x ) increases from 10 μm to 100 μm. With a comprehensive understanding of post-machining DED processes using this numerical modeling procedure, post-treatment techniques can now be tailored to achieve surface residual stress profiles on DED-generated or other additively manufactured metallic components to meet various industrial requirements. • Forces and surface residual stresses are predicted in post-machining of DED-fabricated part. • The model accounts for the cumulative effects of initial residual stress states and grain size. • The initial residual stresses have different effects on forces and final surface residual stresses. • Increasing grain size leads to reduced magnitude of compressive residual stress.
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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) | 0.000 | 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 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".