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ICONE23-1001 THE COMPONENT OPERATIONAL EXPERIENCE DEGRADATION AND AGEING PROGRAM (CODAP) : REVIEW AND LESSONS LEARNED (2011-2014)

2015· article· en· W2632282463 on OpenAlexaffabout
Tudor Dragea, Jovica Riznic

Bibliographic record

VenueThe Proceedings of the International Conference on Nuclear Engineering (ICONE) · 2015
Typearticle
Languageen
FieldDecision Sciences
TopicRisk and Safety Analysis
Canadian institutionsCanadian Nuclear Safety CommissionOntario Tech University
Fundersnot available
KeywordsPipingNuclear powerNuclear power plantAgency (philosophy)EngineeringComponent (thermodynamics)Forensic engineeringReliability engineeringOperations managementMechanical engineeringNuclear physics

Abstract

fetched live from OpenAlex

The structural integrity of piping systems is crucial to continuous and safe operation of nuclear power plants. Across all designs, the pressure boundary and its related piping and components, form one of the many levels of defense in the continuous and safe operation of a nuclear power plant. It is therefore necessary to identify, understand, evaluate and catalogue all of the various degradation mechanisms and failures that affect various piping systems and components across all nuclear power plants (NPP's). This need was first recognized in 1994 by the Swedish Nuclear Power Inspectorate (SKI) which launched a five-year Research & Development (R&D) project to explore the viability of creating an international pipe failure database (SKI-PIPE) (Riznic, 2007). The project was considered to be very successful and in 2002, the Organization for Economic Co-operation and Development (OECD) Pipe Failure Data Exchange (OPDE) was created. OPDE was operated under the umbrella of the OECD Nuclear Energy Agency (NEA) and was created in order to produce an international database on the piping service experience applicable to commercial nuclear power plants. After the successful completion of OPDE, the OECD, as well as other nternational members, agreed to participate in OPDE's successor: the Component Operational Experience Degradation and Ageing Program (CODAP). The objective of CODAP is to collect information on all possible events related to the failure and degradation of passive metallic components in NPP's. With CODAP winding down to the completion of its first phase in December 2014, this report will focus on the conclusions and the lessons learned throughout the many years of CODAP's implementation. There are currently 14 countries participating in CODAP, many of whom are industry leaders (France, Canada, U.S.A., Germany, Japan, Korea etc.). This cooperation on an international scale provides a library of OPerational EXperience (OPEX) for all participating NPP's (Lydell et. al., 2008). CODAP also allows for the sharing of valuable information on a wide range of reactor types such as Pressurized Heavy Water Reactors (PHWR), Pressurized Water Reactors (PWR) and Boiling Water Reactors (BWR). The use of CODAP/OPEX and knowledge databases can and have resulted in a number of significant inspection changes at NPP's worldwide. For example, Canada has already utilized CODAP to address thermal stratification and piping material fatigue issues. Korea has collected and used information for piping failure events to identify sites of potential concern in their in-service inspection programs. Currently there are over 4500 recorded events on pipe failures affecting all ASME Code Classes and non-safety related piping. These events encompass all known modes of damage/degradation and their respective failure modes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.857
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.186
GPT teacher head0.368
Teacher spread0.183 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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
Published2015
Admission routes2
Has abstractyes

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