Determination of LME sensitivity of zinc-coated steels based on the programmable deformation cracking test
Bibliographic record
Abstract
Abstract The current work presents a new test method to evaluate liquid metal embrittlement (LME) susceptibility of zinc-coated steels in arc processes under application-oriented conditions. The procedure is based on the programmable deformation cracking test (PVR test). The PVR test is a variation of a controlled tensile test for hot cracking investigations in arc welding processes. Two dual-phase steels (DP600, DP980) and five transformation-induced plasticity steels (TRIP690, TRIP700, TRIP700, TRIP1100, TRIP1200) were used. The investigations showed that comparable thermo-mechanical loading conditions can be guaranteed for materials of different sheet thicknesses in the PVR test through a targeted adjustment of the heat input per unit length of weld. Furthermore, it was shown that the critical deformation rate $${v}_{cr}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>v</mml:mi> <mml:mrow> <mml:mi>cr</mml:mi> </mml:mrow> </mml:msub> </mml:math> (used for assessing hot cracking susceptibility) may also be used to assess the LME susceptibility of a particular steel. Furthermore, another LME susceptibility parameter, the relative reduction in load-bearing ability $$\Delta\Sigma$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>Δ</mml:mi> <mml:mi>Σ</mml:mi> </mml:mrow> </mml:math> could be derived, which may be used to understand how LME cracking affects materials’ mechanical and fracture properties.
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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 | 0.000 |
| 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 | 0.001 | 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".