Thermo-Mechanical Characterization of Laser Weld 316L(N) Stainless Steel
Bibliographic record
Abstract
316L(N) stainless steel is an austenitic stainless steel variety strengthened by nitrogen through solid solution hardening. The effects of nitrogen on the mechanical properties of 316L(N) SS have not been studied extensively in the past and is the study of current research. The nitrogen content when added to 316L stainless steel in the range 0.07 wt% - 0.21 wt% improves room temperature and high temperature mechanical properties. The loss in strength due to reduced carbon content in 316L(N) SS can be more or less compensated by the addition of nitrogen. Laser welded joints have been fabricated on 316(L)N SS using CO2 laser protecting the environment by employing nitrogen shielding and tested the welded joints under tension at room temperature and at 650 ?C (923 K). In the as - welded condition Transmission Electron Microscope (TEM) revealed the presence of the deformation bands, high density of dislocations and carbides or carbo -nitrides on dislocations near the grain boundary regions which may be in the Heat-Affected Zone(HAZ). At both the test temperatures failure occurred in the base metal by transgranuler mode with the nucleation of cavities. In the present work, laser welding process has proved to be effective in producing satisfactory welded joints.
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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 | 0.000 |
| 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) | 0.001 | 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 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".