Effect of Coating and Welding Wire Composition on AHSS GMA Welds
Bibliographic record
Abstract
Advanced high-strength steels (AHSS) such as complexphase (CP) and high-formability (HF) steel offer weightsaving advantages for automotive applications such as chassis and frame applications. To prevent material oxidation, materials are often galvanized to protect the substrate from corrosion. However, the weldability of coated AHSS becomes challenging due to the trapping of zinc in the weld molten pool, which could lead to weld defects such as porosity and liquid metal embrittlement cracks. This work focused on the weldability of AHSS (CP800 and 980HF) using the gas metal arc welding process. The roles of both galvanized iron coating and filler material on weld strength were investigated. The welds were performed using two different filler materials: a low-strength filler (ER70S-6) and a high-strength filler (ER100S-6) material. In addition, two different joint configurations were studied: lap joints and butt joints. The results showed that the butt joint had a higher strength compared to the lap joints. Furthermore, the strength of the butt joint overmatched the base material strength in all of the tested materials (both in galvanized and uncoated). In general, lap joint strength undermatched the base material strength, which was attributed to the rotation during tensile testing that induced unaccounted bending stress on the lap joint, while using a higherstrength welding wire improved the tensile strength material in the lap joint configuration. The hardness profiles in the 980HF steel also showed a significant hardness mismatch due to the formation of a fully martensitic microstructure in the heat-affected zone, which led to suppressing the deformation across the lap joint.
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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 | 0.000 | 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) | 0.000 | 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".