Investigating Weld and HAZ Effects During SMAW of Pipe and Fitting Materials
Bibliographic record
Abstract
Abstract The primary goal of weldments is to have the longitudinal strain not concentrated in the weld. To date, there is no reliable way to accurately predict this, given the variability of welding techniques, mechanical properties, and manufacturing methods of materials in CSA Z662 pipeline designs. Several girth welds were completed using SMAW on common carbon steel pipe and fittings used under CSA Z662 designs. The results focus on comparing as-welded joint properties relative to the base metal. The base materials were chosen to be wide ranging in chemistry and manufacturing process. The deposited weld filler metal tensile strength can be relatively and consistently predicted; however, the overall weldment properties are more difficult to estimate. The results provide an opportunity to learn more about the response of welding on the base metal. The goal is to improve the ability to design and complete weldments that have equal or better mechanical properties than the base metal. Advancements are already being made to new construction best practices, but there is value in understanding how conventional filler metals and base metals are allocated to highest risk welds for new construction and existing assets.
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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 | 0.001 |
| 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) | 0.001 | 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".