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Enregistrement W6912885123 · doi:10.5281/zenodo.7147604

Mooring systems integrity management technologies

2020· article· en· W6912885123 sur OpenAlexaff

Notice bibliographique

RevueZenodo (CERN European Organization for Nuclear Research) · 2020
Typearticle
Langueen
DomaineComputer Science
ThématiqueEnvironmental Engineering and Cultural Studies
Établissements canadiensIntecsea (Canada)
Organismes subventionnairesHorizon 2020 Framework Programme
Mots-clésMooringIntegrity managementTurbineDowntimeLeverage (statistics)Structural integrityOperating expenseHull

Résumé

récupéré en direct d'OpenAlex

The MooringSense project aims to reducing OPEX and increasing efficiency of FOWT through the development of efficient risk-based integrity management strategies for mooring systems based on a cost effective and reliable on-line monitoring technology and digital twin. This deliverable provides an overview of the state-of-the-art of current technologies, tools and techniques related to integrity management of mooring systems currently applied to the O&G industry, from the perspective of FOW, with the aim of identifying the technological gaps applied to the integrity management of mooring systems. In the first instance, it shall be highlighted that the purpose of a mooring system in both O&G and FOW is station keeping, namely to keep a floating structure within reasonable proximity of a designated location and to avoid excessive movement that will hinder safe operation. In the O&G industry, mooring systems have been utilized for many years and there is a level of understanding of vessel motion and wave interaction that is significantly higher compared to the concepts employed by the floating offshore renewables sector. Although this can be seen as a weakness, the FOW industry can leverage the O&G experience to ensure that reliable and cost-effective solutions are employed. However, a key difference when comparing a mooring system for a traditional O&G installation (i.e. a semisubmersible or an FPSO) and a FOW farm is in the number of mooring lines. A traditional O&G installation will generally comprise of a limited number of mooring lines (i.e.10-30); however, for a medium size FOW of 50 FOWT, each turbine will have 3 to 6 mooring with a total number in the range of 150-300. Given the high cost of offshore operations (inspection, maintenance, repairs) it is of vital importance that a cost-effective integrity management strategy is implemented to keep OPEX at an acceptable level. This deliverable details the key aspect related to integrity management of mooring system including degradation mechanism in chain, wire ropes and synthetic ropes; inspection and integrity management techniques; failure detection, line tension monitoring, control algorithms and digital twin. In addition, the deliverables highlight some technological gaps, which are summarised below: With regards to international standards and guidelines, there is a clear need for tailored documentation focusing on the challenges of FOW and, in particular, there is the need of a tailored risk-based approach that can be applied to the FOW industry to enhance the effective operation of the floating structures whilst reducing costs. SHM for monitoring the integrity of FOW substructures is in the development phase. First systems are available on the market, but there are reasonable doubts regarding their reliability and robustness, and local inspection remains necessary for making decisions on O&M. Effective mooring line failure detection systems are still required. Work on the exploitation of novel sensors such as those proposed in this project is not abundant, for obvious reasons. More generally, the relationship between turbine control, platform position and mooring line loads requires careful study. Several monitoring technologies are available today to provide mooring line tension measurements in floating platform as a source of information for integrity assessment and management. However, these technologies present several issues related to robustness and reliability, as well as costs if they are to be applied to FOW, where long term operation and low cost are mandatory requirements Designing and implementing a Digital Twin of a mooring line requires simultaneous adoption of several technologies and tools. Some of these technologies are still at early stage of development however are evolving at fast pace.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,024
Score d'incertitude au seuil0,082

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,003
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0030,001
Études des sciences et des technologies0,0010,001
Communication savante0,0040,005
Science ouverte0,0030,005
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0240,018

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.

Tête enseignante Opus0,038
Tête enseignante GPT0,205
Écart entre enseignants0,167 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

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