A Procedure to Include the Fatigue Effects of Thermal Gradients in a B31.1 Butt Weld of Dissimilar Metals and Welding End Transition Joint (TTJ) of Similar Metals for Design and Plant Life Extension
Bibliographic record
Abstract
Fatigue evaluation in B31.1-2007 is currently done based on B31.1 Equations 1 & 2 and generally considers only the stress due to displacement load ranges as per Equation 13. Yet, fatigue damage is also occurring due to pressure cycling and thermal gradients. To exacerbate this, power plant design pressures and temperatures are rising, new materials are being introduced, pipes and attached components are becoming increasingly thick, and owners are requiring power plants to heat-up and cool-down at faster rates. Also, power plant owners are more and more interested in extending the life of power plants beyond their original design life. This paper addresses the pressing need in today’s power plant environment for additional fatigue evaluation by providing a procedure for assessing an as-welded Butt weld of dissimilar metals and a Weld End Transition (or TTJ) (B31.1-2007 Figure 127.4.2) of similar metals to include the effects of thermal gradients calculated as per ASME Section III-2007 Subarticle NB-3600. The disadvantage of this approach is that the conservatism in the calculation of these thermal gradient stress intensities may produce unacceptable results. In that case, the assessment is a warning that something else needs to be done by way of either monitoring or modifying the thermal operation or more rigorous evaluation. The advantage of this methodology is that it will ensure a fatigue failure does not occur any sooner due to the effects of thermal gradients than would otherwise occur due to other factors. It maintains the traditional B31.1 approach to fatigue with the same limit of SA except that there is now an additional term, STG, to account for the fatigue contribution due to thermal gradients. Considering the effects of these thermal gradients in this way will further help to preserve the integrity of the piping pressure boundary and consequently, the safety of personnel in today’s power plants and into the future.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".