Resistance spot weldability and high cycle fatigue behaviour of martensitic (M190) steel sheet
Bibliographic record
Abstract
Resistance spot welding characteristics of martensitic sheet steel (M190) was investigated using a peel test, microhardness test, tensile shear test and fatigue test. Tensile shear test provides better spot weld quality than conventional peel test and hardness is not a good indicator of the susceptibility to interfacial fracture. Unlike DP 600 steel, the maximum load carrying capability is affected by the mode of fracture. At high load low cycle range, weld parameters have a significant difference in the S–N curves. But, almost similar fatigue behaviour of the spot welds is noted at low load high cycle range. However, when applied load was converted to stress intensity factor, the difference in fatigue behaviour between welds and even DP 780 steel diminished. Furthermore, a transition in fracture mode, that is, interfacial and plug and hole type at about 50% of yield load were observed.[* Note: Correction made on 16 Aug 2010 after first publication online on 28 June 2010. The authors' affiliations were corrected. Under Results and Discussion, in reference to the HAZ hazardness in the ‘Micro hardness profile’ section, Figure 2 was changed to Figure 3. In reference to the welding parameters under ‘Tensile properties’ section, note that Figure 4 represents 7/200 and Figure 5 represents 5/300. In reference to the low cycles behaviour of S-N curves in the ‘Fatigue’ section, Figure 5 was changed to Figure 6.]
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".