Effect of Heat Input on Weldability of Low Nickel High Manganese Stainless Steel.
Bibliographic record
Abstract
The effect of heat input on the microstructure and mechanical properties of low nickel-high manganese stainless steel welded using a shielded metal arc was investigated. Six samples divided equally into two groups that represented the two distinct degrees of heat input were conducted: low heat (128 J/mm- 139 J/mm-165 J/mm) and high heat (182 J/mm -207 J/mm- 225 J/mm), respectively. These groups were subjected to microstructural analyses and tensile tests to see how heat input affected their joints' mechanical characteristics and microstructure evolution. In the second group, the high value of the ultimate tensile strength (UTS) was found in the case of the high-heat input (182 J/mm) sample. Macrostructure observations were made at the melting zone for each sample. In the case of low heat input formation, partial penetration was observed. However, in the case of high heat input formation, full penetration was observed in all samples treated to the various heat inputs. No defects, such as cracks or voids, were found. In addition, it was observed by increasing heat inputs that the average inter-dendritic spacing in the weld zone increased, which plays a significant role in the observed changes in the tensile characteristics of the welded samples.
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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 | 0.000 | 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) | 0.002 | 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".