Coke Drum Keyhole Optimization With Alloy Weld Overlay
Bibliographic record
Abstract
Abstract Coke drums are subjected to severe cyclic thermal and structural loading, and have therefore become canonical examples of thermo-mechanical fatigue failure. One of the most common locations of fatigue failure is at the skirt-to-shell attachment weld. To increase the fatigue life of the attachment weld, vertical slots and keyholes are often machined in a circumferential pattern near the top of the skirt to increase local flexibility near the weld. While this methodology provides a cost-effective means to improve the fatigue life of the attachment weld, stress concentrations that form at the keyholes result in crack initiation and propagation. As such, frequent repairs are necessary to prevent crack growth at the keyhole locations. In the present investigation, a new keyhole design consisting of N06625 overlay at the keyhole locations as a means of delaying crack initiation has been studied using FEA simulations. To further optimize the new design, a sensitivity study involving keyholes with and without fillets was also performed to determine the effect of fillet size on fatigue life. The results presented herein indicate that increasing the keyhole fillet radii mitigates the effect of stress concentrations on the corners of the keyholes, which delays crack initiation. Furthermore, it has been demonstrated that adding N06625 overlay at the keyhole protects the base metal from excessive plastic strain. In particular, the proposed design has been shown to improve the fatigue life of the keyhole by at least an order of magnitude when compared to analogous keyhole designs with no overlay, which has the potential to improve the overall cost-effectiveness of keyhole implementation by a significant margin.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".