Development of a Thermomechanical Model for Prediction of Residual Stress during Laser Powder-Bed Fusion: Evaluation of Inherent Strain Approach
Bibliographic record
Abstract
The build-up of residual stresses in a part during laser powder-bed fusion (LPBF) provides a significant limitation to the adoption of this process. These residual stresses may cause a part to fail during a build or fall outside the specified tolerances after fabrication. Defectfree production of metallic parts using LPBF requires process optimization, as a crucial step, for effective usage of the process. Development of a numerical model to accurately predict the induced residual stresses and distortion during the LPBF process is of great interest as it allows to effectively investigate the influence of processing parameters on the quality of the parts. In this work, we developed a novel high-fidelity finite element (FE) model based on the inherent strain (local-global) approach to simulate the build process and calculate the residual stress and distortion for Hastelloy X specimens built with a continuous scan strategy. Conclusions from the thermomechanical simulations showed good agreement with X-ray diffraction measurements and 3D scanning data used to determine the residual stresses and distortions in the 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 | 0.000 | 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 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".