The Development and Use of an Absolute Depth Size Specification in ILI-Based Crack Integrity Management of Pipelines
Notice bibliographique
Résumé
To provide a more insightful and accurate feature description from Crack In-line Inspection (ILI) reporting as per the Fitness For Service analysis in API 1176, individual crack dimensions must be established to a given accuracy. PII Pipeline Solutions established an absolute depth sizing specification conforming to the dig verification processes of API 1163. This change represented a significant shift from a traditional reporting format for depth sizing in “bands” of 1–2 mm, 2–3 mm and > 3 mm depths within crack ILI inspection reporting. When assessing features with characteristics stated in a sizing band, the pipeline integrity assessment approach required a conservative assumptions that all of the features in that band must be treated as if they are in the deepest band value. The implication then meant that the specification created only 3 sizes of crack depths 1–2 mm, 2–3 mm, > 3 mm (± 0.5mm tolerance at 90% certainty). In practical terms a large quantity of features in the significant band of 2–3 mm must be treated as potential dig candidates with a depth of at least 3 mm, making length characteristics as the only severity ranking basis for any priority dig selection. Previous attempts at establishing absolute depth sizing for crack inspection required a series of calibration digs. The large sample size over multiple inspection runs and pipeline sections allowed for a statistical specification algorithm is developed as part of the analysis process, therefore no additional reporting time, or excavation cost was involved. The new absolute sizing algorithm has provided operators with a means of prioritizing digs, based upon individual feature length and depths. Replacing the traditional depth bands with individual feature specific peak depths and thereby providing a major step forward in achieving a cost effective process of prioritizing crack mitigation in pipelines. Following the dig verification process in API 1163, significant populations of infield NDE results were utilized on a variety of pipeline sections of different diameters. Predicted absolute depth estimation accuracy was determined for specific feature types and thereby created a depth tolerance, with statistical certainty levels established that match those available and recognized with metal loss ILI. This paper describes the process and the means by which an absolute depth crack ILI specification was established using characteristics from a significant set of real features. It also describes benefits realized within pipeline integrity engineering of moving to such a new reporting protocol.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».