A detailed investigation of induced residual stresses in the laser powder bed fusion process using the modified inherent strain approach and experimental measurements
Bibliographic record
Abstract
In this work, a multiscale finite element model is proposed to simulate the Laser Powder Bed Fusion (LPBF) process, employing the Modified Inherent Strain (MIS) methodology. MIS is a more sophisticated approach than the conventional Inherent Strain (IS) technique, initially developed for welding process simulations. Due to the complicated thermo-mechanical interactions present in the metal Additive Manufacturing (AM) process, the MIS approach has evolved to deal with it, in which sequentially deposited layers act as mechanical constraints on earlier layers, influencing stress and strain evolution throughout the process. A multiscale modeling approach can effectively predict the residual stresses induced during LPBF, which are essential for assessing the quality and performance of the manufactured part. This study provides a novel contribution by systematically validating MIS-based residual stress predictions against depth-resolved X-ray diffraction (XRD) measurements up to 3 mm below the surface, addressing a critical gap in the literature where prior works primarily focused on surface-level stress or distortion. Laser power and velocity, which are critical process parameters, were modified to investigate their individual impacts on the residual stress distribution in the longitudinal and transverse directions. Simulated results were validated through experimental XRD measurements on fabricated Inconel-625 test coupons. While the MIS method aligns well with the experimental data at the surface level, discrepancies arise in deeper subsurface layers, where simulations tend to underestimate tensile residual stresses. This indicates that additional refinement, such as thermal-microstructural coupling, may be necessary to enhance stress prediction accuracy in multi-layer AM processes. By offering a comprehensive depth-resolved analysis, this work provides new insights into subsurface stress evolution, critical for ensuring the structural integrity of LPBF parts. The study provides a critical assessment of the MIS method’s capabilities and provide essential guidance for future research opportunities to improve residual stress predictions in LPBF-produced parts.
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How this classification was reachedexpand
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 | 0.001 | 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 teacher head, 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".