An Investigation into Strain Partitioning in Mismatched HSLA-65 Steel Welds
Bibliographic record
Abstract
The aim of this study was to quantify strain partitioning in HSLA-65 joints, welded with three types of weld filler: 6011 undermatched weld filler, 7018 matched weld filler, and 9016 overmatched weld filler. Strain measurements were made using a three-dimensional digital image correlation system while specimens were tested on a displacement controlled servo-hydraulic test frame. Crosshead displacement rates ranged from 0.056 mm/s to almost 56 mm/s. Coupons were cut from flux-core arc welded HSLA-65 plates to characterize the base metal, weld filler materials, and mismatched welds. Constitutive material properties could be extracted reliably for all coupons at the lowest displacement rate and showed that, as expected, all weld fillers had similar elastic modulus values but different yield strengths. A comparison of the peak strains at 85 per cent of maximum elongation showed that overall the failure strain was inversely related to the crosshead displacement rate. Analysis of the mismatched coupons found that the failure location was a function of weld filler and was independent of strain rate. Higher magnification imaging of the weld nugget showed that strain partitioning occurred within the weld zone, with slightly lower strains in the cap pass as opposed to the root pass.
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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 | 0.001 | 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) | 0.001 | 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".