Mechanical properties and microstructure of additively manufactured stainless steel with laser welded joints
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Bibliographic record
Abstract
Powder bed fusion (PBF) is a commonly employed metal additive manufacturing (AM) process in which components are built, layer-by-layer, using metallic powder. The component size is limited by the internal build volume of the employed PBF AM equipment; the fabrication of components larger than this volume therefore requires mechanical joining methods, such as laser welding. There are, however, very limited test data on the mechanical performance of PBF metal with laser welded joints. In this study, the mechanical properties of PBF built 316L stainless steel parts, joined together using laser welding to form larger components, have been investigated; the microstructure of the components has also been examined. 33 PBF 316L stainless steel tensile coupons, with central laser welds, welded using a range of welding parameters, and with coupon half parts built in two different orientations, were tested. The porosity, microhardness and microstructure of the welded coupons, along with the widths of the weld and heat-affected zone (HAZ), were characterised. The PBF base metal exhibited a typical cellular microstructure, while the weld consisted of equiaxed, columnar and cellular dendrite microstructures. Narrow weld regions and HAZs were observed. The PBF base metal was found to have higher proof and ultimate strengths, but a similar fracture strain and a lower Young’s modulus, compared with conventionally manufactured 316L stainless steel. The strengths were dependent on the build direction – the vertically built specimens showed lower proof strengths than the horizontal specimens. The laser welds generally exhibited lower microhardness, proof strengths and fracture strains than the PBF base metal which correlated with the observed structure. This work has demonstrated that PBF built parts can be joined by laser welding to form larger components and provided insight into the resulting strength and ductility.
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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) | 0.001 | 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 it