Effect of Beam Oscillation Patterns on Laser Welding of 304L Stainless Steel: An Experimental and Modeling Study
Bibliographic record
Abstract
Laser welding is increasingly recognized for its precision and efficacy, particularly in handling complex materials like 304L stainless steel. This study investigates the impact of various laser welding parameters, including laser power, welding speed, and beam oscillation patterns (sinusoidal, square, and triangular), on the quality of welded joints. Using the Taguchi method, we structured an L9 experimental design to analyze these parameters systematically. The key findings revealed that beam oscillation patterns significantly influence both the microhardness and tensile strength of the welds. Notably, square and sinusoidal patterns achieved higher microhardness values than triangular patterns, which correlated with their differing impacts on the weld's mechanical properties. Further analysis using analysis of variance (ANOVA) and regression models validated the critical roles of laser power and welding speed, offering predictive insights into optimizing welding conditions for enhanced joint integrity. This study provides a foundational approach for tailoring laser welding settings to improve weld quality in industrial applications, contributing to the body of knowledge with specific data on the effects of beam oscillation in 304L stainless steel welding.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".