Integrity Assessment of Spherical Pressure Components With Local Corrosion and Hot Spots
Bibliographic record
Abstract
Corrosion damage and hot spots are typical of damages that can occur in ageing pressure vessels and pipelines used in industrial processes. Internal and external corrosion could be the result of corrosive products stored inside or harsh environmental conditions on the outside. Hot spots are caused by damage due to loss of refractory lining on the inside wall of pressure components or due to maldistribution of flow containing catalyst and reactive fluids. The structural integrity of such ageing components needs to be evaluated periodically to establish the continued suitability of the vessels under operating conditions. The present paper develops a method for Level 2 (as categorized by API 579) structural integrity evaluations of spherical pressure vessels containing local corrosion damage or hot spot. The decay lengths for spherical shells subject to local damages have been studied based on stretching and bending effects using elastic shell theories so as to identify the reference volume participating in plastic action. A limit for “local” corroded spot or hot spot is defined by the size of damage that an onset of pure membrane action occurs inside the damaged area. The size of damage indicating the crossover from dominance of stretching effects on the damage behavior to that of bending effects is also presented. The lower bound recommended “remaining strength factors” for spherical pressure vessels containing corrosion or hot spot are formulated by application of Mura’s integral mean of yield criterion and the improved lower bound mα-multiplier. Three alternative recommendations are proposed. The effectiveness of the proposed methods is evaluated and demonstrated through illustrative examples and comparison with inelastic finite element analyses.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".