Pipeline Integrity Management: An Approach to Geotechnical Risks
Bibliographic record
Abstract
Linear works, such as highways, power lines, gas and oil pipelines among others, as well as other types of engineering works can be threaten by natural hazards, such as landslides, floods, erosions, earthquakes, hurricanes, seaquakes and others, which may lead to great environmental impacts, very high sum of money lost and even deaths. Aiming to reduce geological and geotechnical risks, preventive or corrective actions can be executed from the design phase to the operational and maintenance stages in pipelines. In the last phase, an integrity management plan can be adopted to mitigate residual risks not covered on the design and construction phases. One of the alternatives to implement a gas pipeline integrity management is found in the code “Managing System Integrity of Gas Pipelines” – ASME B31.8S (2005). However, this code has some limitations in actions concerning to prevention, identification and correction of geological and geotechnical problems. This paper presents information about geotechnical risks in transmission pipelines and tools applied in identification, prevention and correction of geotechnical problems in pipelines, as well as, others that can potentially be applied in pipelines. A basic pipeline integrity management plan focused on geotechnical risks is proposed in the paper, transcribed as a contribution to ASME B31.8S Code. This plan is composed by actions: from identification, prevention, evaluation and analysis to correction of geotechnical instabilities in pipelines. It is composed by a flowchart with all actions selected for the geotechnical risk care. The plan was developed based on directions set in ASME B31.8S Code, including Brazilian, Italian and Canadian experiences.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".