Experimental and numerical investigation on the effect of layer thickness during laser powder-bed fusion of stainless steel 17-4PH
Bibliographic record
Abstract
Layer thickness is one of the most important input process parameters in laser powder-bed fusion (LPBF) additive manufacturing (AM) since it directly affects the defects found in the printed products, such as porosity, cracks, and manufacturing rate. In this work, three-dimensional finite element heat transfer model was employed to compare and evaluate two different powder layer thicknesses (20 μm and 40 μm) at varying laser power and scanning speeds. A layer-thickness dependent laser absorptivity approach was considered to improve the prediction accuracy of the proposed model. Single track experiments with stainless steel 17-4PH were conducted to validate the simulation model. Simulation results show good agreement with the experimental results with different layer thicknesses. The corresponding averaged melt pool error for width and depth were 4.2% and 9.1%, respectively. It is found that the melt pool dimensions with different layer thicknesses are similar for the most part with slight variations in the melt pool dimensions using varying laser power and scanning speed. However, the morphology of the melt pool track shows visible changes between different thicknesses.
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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".