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Record W2767049430 · doi:10.1115/pvp2017-66150

Solution of a Sample Problem Related to Revision 1 of Code Case N-830

2017· article· en· W2767049430 on OpenAlexaff
Mark Kirk, Steven X. Xu, Cheng Lui, Marjorie Erickson, Yil Kim, Darrell Lee, Do Jun Shim, Gary L. Stevens

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsKinectrics (Canada)
Fundersnot available
KeywordsPipingSample (material)Code (set theory)Fracture toughnessPressure vesselPercentileDocumentationEngineeringMathematicsComputer scienceMechanical engineeringStatisticsMaterials scienceProgramming languageComposite materialThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Within the American Society of Mechanical Engineers (ASME) the Section XI Working Group on Flaw Evaluation (WGFE) is currently working to develop a revision to Code Case (CC) N-830. CC N-830 permits the direct use of fracture toughness in flaw evaluations as an alternative to the indirect/correlative approaches (RTNDT-based) traditionally used in the ASME Code. The current version of N-830 estimates allowable fracture toughness values in the transition regime as the 5th percentile Master Curve (MC) indexed to the transition temperature T0. The proposed CC N-830 revision expands on this capability by incorporating a complete and self-consistent suite of models that describe completely the temperature dependence, scatter, and interdependencies between all fracture metrics (i.e., KJc, KIa, JIc, J0.1, and J–R) used currently, or useful in, a flaw evaluation for conditions ranging from the lower shelf through the upper shelf. Papers presented in previous ASME Pressure Vessel and Piping (PVP) Conferences since 2014 provide the technical basis for these various toughness models. This paper contributes to this overall CC N-830 documentation suite by presenting the results of a sample problem run to assess the proposed revision of the CC. The objective of the sample problem was (1) to determine if the revised CC was written with adequate clarity to permit different engineers to accurately and consistently calculate the various allowable toughness values described by the equations in the CC, (2) to assess how these allowable toughness values would be used to calculate allowable flaw depths using standard ASME SC-XI approaches, and (3) to compare allowable flaw depths calculated using established Code practices (RTNDT-based) to those calculated using proposed CC practices (T0-based). The sample problem demonstrated that (1) the CC was written with sufficient clarity to allow different engineers to arrive at the same estimated value of allowable toughness, (2) the latitude associated with the provisions of the ASME Code pertinent to estimation of allowable flaw depth are responsible for some differences in the allowable flaw depth values reported by different participants, and (3) current Code estimates of allowable flaw depth are far more conservative (that is: smaller) than values estimated by the candidate CC methods based on the MC, this mostly due to the generally-conservative bias of the Code’s RTNDT & KIc approach. The candidate CC methods provide much more consistent conservatism than current Code approaches for all conditions in the operating nuclear reactor fleet via their use of an index temperature (T0) defined by actual fracture toughness data and a temperature dependence defined by those data. The WGFE is continuing to evaluate candidate approaches to estimate allowable toughness values for CC N-830 using a T0-indexed Master Curve. Associated work is addressed by two companion papers presented at this conference.

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)0.006
metaresearch head score (Gemma)0.053
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: Other · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.053
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0090.002

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 head0.022
GPT teacher head0.262
Teacher spread0.241 · 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
GenreOther

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

Citations2
Published2017
Admission routes1
Has abstractyes

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