MOP, MAOP, DP and MAWP: Understanding the Differences to Avoid Unnecessary Costs
Bibliographic record
Abstract
The ASME pressure vessel and piping codes and standards provide excellent references for code writers in international jurisdictions when developing their own national codes and for safety authorities when developing regulatory acts. The inclination to customize this effort may add unnecessary complexity that unintentionally obscures the underlying engineering principles. In developing the Canadian pipeline code, the authors use the notion of maximum operating pressure or MOP similar to the MOP found in the ASME codes for pipelines. While the ASME code definitions are explicit and articulate, the MOP defined in the Canadian code is less so and has led to inadvertent confusion by industry users. Misunderstanding of complementary terminology used in ancillary ASME standards has contributed to further complexities. The use of the term, maximum allowable operating pressure or, MAOP in the ASME pipeline codes has further reduced clarity when integrating this term into international codes and regulatory acts. This paper examines, in detail, some aspects of the Canadian pipeline code and illustrates via a representative case study some of the aforementioned difficulties that have arisen. These difficulties resulted in unnecessary derating of assets by imposing operational limits that were well below actual capacity. A clear explanation of the engineering principles underlying the provisions for codes which use a “design by rules” philosophy will help operators set appropriate limits for both static and dynamic loads that may not be apparent in the specific codes considered and will be expository for regulators and code users in general.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.018 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| 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".