Hybrid GTAW–FCAW of 316L Stainless Steel Pipes: Influence of Oxygen Content in Baking Gas and Surface Preparation on Oxide Characteristics and Corrosion Behavior
Bibliographic record
Abstract
This study investigates the combined effects of oxygen content in the purging gas and pre-weld surface finish on the discoloration and corrosion resistance of AISI 316L pipe joints, with relevance to pipe welding where internal cleaning is constrained. The hybrid GTAW–FCAW process was used. Welds were produced at two oxygen levels (500 and 5000 ppm) and two finishes (40- vs. 60-grit). Discoloration and oxide morphology were examined by SEM/EDS, and corrosion behavior was evaluated without oxide removal using cyclic polarization and electrochemical impedance spectroscopy. The results reveal that higher oxygen levels in the purging gas produced more porous, less protective oxide layers, along with intensified oxidation around surface defects such as micro-holes. Surface roughness was also found to influence corrosion behavior: rougher surfaces exhibited higher resistance to pit initiation, whereas smoother surfaces were more susceptible to initiation but offered greater resistance to pit propagation. The corresponding governing mechanisms were identified and discussed in terms of how surface preparation affects crystallographic texture, heterogeneities and recrystallization. Taken together, the results link oxide morphology and near-surface microstructure to electrochemical response and offer practical guidance for pipe welding when internal cleaning is constrained, balancing purging control with surface preparation to preserve corrosion performance. The findings further highlight the critical roles of both purging-gas composition and surface preparation in the corrosion performance of stainless steel welded pipes.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".