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Record W2327427453 · doi:10.1115/pvp2012-78130

A Review and Remediation of a Code Non-Compliance Incident: Lessons Learned

2012· review· en· W2327427453 on OpenAlexaff
John J. Aumuller, Zihui Xia, Vincent A. Carucci

Bibliographic record

VenueVolume 1: Codes and Standards · 2012
Typereview
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCode (set theory)Code reviewReworkComputer scienceProcess (computing)Software engineeringConfusionEngineering design processEngineeringRisk analysis (engineering)Static program analysisSoftwareSoftware developmentProgramming languageBusinessMechanical engineering

Abstract

fetched live from OpenAlex

The ASME Codes address the needs of industry and the public for the construction of safe equipment for pressure containment. The two basic philosophies underlying the requirements of the ASME VIII sections are “rules based” design versus “design by analysis”. Code contributors have written extensively on the need for Code users to apply common sense when using the Code. This message is often lost in the confusion when atypical mechanical design details have been intentionally or inadvertently used. Those atypical design details that can be identified during the review process can be easily resolved; details that are discovered after construction completion and, worse yet, just prior to operation can be devastating to a project. The Code places emphasis on education, experience and the use of engineering judgment but, these can never be used to overrule mandatory requirements or specific prohibitions of the Code. A specific incident is reviewed wherein the regulatory authority of the jurisdiction intervened and de-registered a vessel design due to Code non-compliance. Although the deficient detail was thought to be better, based on consideration of engineering principles, than the detail strictly meeting Code requirements, the as-constructed detail was rejected by the regulatory authority. Extensive field rework ensued to modify the detail to conform to Code, and of course the costs were very high. This paper reviews the engineering issues, illustrates the motivation for the Code requirements, and serves as a reminder to Code users to be vigilant in the details of Code construction.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.035
metaresearch head score (Gemma)0.123
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.186

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.123
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0090.005
Scholarly communication0.0060.007
Open science0.0040.005
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0020.002

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.

Opus teacher head0.071
GPT teacher head0.340
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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Same venueVolume 1: Codes and StandardsSame topicOffshore Engineering and TechnologiesFrench-language works237,207