Application of Code Case N-597 for Local Thinning Assessment for Class 1 Piping
Bibliographic record
Abstract
Process piping components such as elbows, bends and tees experience local wall thinning due to Flow Accelerated Corrosion (FAC). Fitness for service studies of the piping components that are affected by FAC for continued operation have gained importance in light of the plant life extension resulting in economic benefits for the operating utilities. ASME Code Case N-597 provides the guidelines for acceptance for continued service of Classes 2 and 3 piping components experiencing wall thinning during operation. However, for Class 1 systems, the Code Case recommends that the owner develop the methodology and criteria for the assessment of wall thinning. This paper establishes a criteria and methodology for the assessment of thinned Class 1 piping system components. The rules of NB-3221 and NB-3650 of ASME Boiler & Pressure Vessel Code (Ref.1) have been considered in establishing the criteria. The requirements of NB-3221 have been utilized for evaluating the adequacy of pressure design. After meeting this requirement, further evaluation of the piping with thinned area is carried out as per NB-3650 requirements for all loadings corresponding to design and service conditions. To illustrate the criteria and the methodology, an assessment of a sample problem of a locally thinned region in a pipe bend is provided in this paper. Finite element analysis and piping analysis are used for the assessment of the thinned region of the pipe bend. Loading considered includes pressure, deadweight, thermal transients and seismic effects.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".