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Record W2008577916 · doi:10.1115/ipc2004-0057

Quantitative Evaluation of Indirect Inspection Reliability and Pipeline Reliability Based on Statistical Methods

2004· article· en· W2008577916 on OpenAlex
James Mihell, David Coleman, Ryan Sporns

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venue2004 International Pipeline Conference, Volumes 1, 2, and 3 · 2004
Typearticle
Languageen
FieldEngineering
TopicStructural Integrity and Reliability Analysis
Canadian institutionsManitoba HydroDynamic Systems Analysis (Canada)
Fundersnot available
KeywordsReliability (semiconductor)Reliability engineeringPipeline (software)CorrosionInterval (graph theory)Consistency (knowledge bases)Computer sciencePipeline transportForensic engineeringEngineeringMaterials scienceMathematicsArtificial intelligence

Abstract

fetched live from OpenAlex

To support an External Corrosion Direct Assessment (ECDA), Indirect Inspections were performed on a 44 km section of NPS 6 extruded polyethylene coated natural gas pipeline. Based on previous investigations of the pipeline, external corrosion defects were known to have occurred at coating holidays. Such holidays can often be detected using current voltage gradient surveys and close interval surveys. Two successive ACVG surveys over the pipeline were preformed. In addition, Close Interval Survey data were considered in order to complete the Indirect Inspection dataset. Statistical analysis methods were developed and employed against the data generated from these surveys so that the following objectives could be met: 1. Assess the reliability of the Indirect Inspection technique in terms of its ability to locate coating holidays and hence, its ability to locate potential corrosion features; and, 2. Assess, in quantitative terms, the reliability of the pipeline in terms of its potential for failure, and quantitatively establish the impact that the Indirect Inspection and dig program had in improving that reliability. In completing the first objective, duplicate survey results were compared with Direct Examination results. The statistical analysis provided a means of estimating technique reliability, which was conservatively estimated at 96%. Subsequent evaluation of factors affecting technique reliability indicated that the density of indications and consistency of applying the Indirect Inspection technique had a bearing on the overall reliability. The second objective was completed by applying the results of the Indirect Inspection reliability study to a statistical analysis of corrosion incidence data and corrosion size distributions that were derived from the Direct Examination data. Pipeline reliability was quantitatively expressed as a function of year of operation and the reliability of the Indirect Inspection technique. For the case examined, the Indirect Inspection techniques that were applied were found to increase pipeline reliability by approximately an order of magnitude.

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.

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)0.002
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.350
Threshold uncertainty score0.871

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
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 science0.0000.000
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 head0.036
GPT teacher head0.340
Teacher spread0.304 · 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