Benchmarking of print properties and microstructures of 316L stainless steel DMLS prints
Bibliographic record
Abstract
Abstract Direct metal laser sintering (DMLS) is an established technology in metal additive manufacturing. This complex manufacturing process yields unique as-built material properties that influence mechanical performance and vary with different machine parameters. Part porosity and residual stresses, which lead to part failures, and grain structure, as it relates to mechanical properties and anisotropy of DMLS parts, require investigation for different print settings. This work presents results for density, residual stress, and microstructural inspections on designed test artifacts for the benchmarking of 3D metal printers. Results from printing artifacts on two separate DMLS printer models with default parameters show highly dense parts for both printers, with relative densities above 99.5%. Characterization of residual stress through cantilevered deflection specimens indicates similar resulting thermal stresses developed in both build processes, with deflection averages of 32.48% and 28.09% for the respective machines. Additionally, properties of the test artifact printed after adjusting default machine parameters for equal energy density are characterized.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".