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Record W2098253561 · doi:10.1115/ipc2010-31645

Spill Consequence Analysis: A Method to Prioritize Integrity Excavations of Liquid Pipelines

2010· article· en· W2098253561 on OpenAlexaboutno aff
Jana M. Haggins, Edgar Ivan Cote, Kristine Morgan, Ehab M. Shaheen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStructural Integrity and Reliability Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsIntegrity managementPipeline transportEnvironmental sciencePipeline (software)ExcavationCorrosionRisk analysis (engineering)Forensic engineeringPetroleum engineeringComputer scienceGeologyEngineeringGeotechnical engineeringEnvironmental engineeringMaterials science

Abstract

fetched live from OpenAlex

Corrosion and stress corrosion cracking (SCC) control programs are elements of pipeline integrity management. These programs often include in-line inspections (ILI’s) to identify, characterize and size anomalies, followed by field excavations to repair defects, remediate coating failures, and establish tool sizing accuracy. The highest priority excavations target anomalies with the lowest predicted remaining strength or deepest flaws. In cases where loss of pipeline integrity is highly consequential, selection of additional excavation sites based on the risk of failure is warranted. As specified in Annex B of CSA Z662-07, the risk of failure combines probability (typically based on the predicted remaining life of known corrosion or cracking features) with an evaluation of consequence along the pipeline length. Consequence evaluation typically considers the impacts of health and safety, environmental, property damage, public disruption, service interruption and financial loss. A practical methodology for evaluating consequence for liquid pipelines was developed for the NPS 10 Alberta Products Pipeline (APPL) in Alberta, Canada. Comprising of three (3) parts, the methodology starts with an evaluation of spill volume along the pipeline based on valve closure times and pipeline inventory drawdown. Combined with soil absorption data and topography, the spill volumes are used to model spill areas along the pipeline. Finally, the spill areas are overlaid on a classification of land use along the pipeline to quantify the relative spill consequence. The land use classification developed for this analysis has commonalities with the definitions for High Consequence Areas (HCA) and Unusually Sensitive Areas (USA) within U.S. Code of Federal Regulations (49 CFR, Part 195). Prioritized segments of the pipeline with elevated consequence levels were identified and used with the probability of failure to calculate risk and prioritize sites for ILI excavation programs.

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.002
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.018
GPT teacher head0.303
Teacher spread0.284 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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
Published2010
Admission routes1
Has abstractyes

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