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3D spatial modelling of CPT data for probabilistic preliminary assessment of potential pile tip damage upon collision with boulders

  • Tip damage of monopiles from boulder collisions during installation has emerged as a critical design issue, primarily due to the combination of the widespread use of large-diameter piles and the complexity of the ground conditions at the available sites. Recently, a framework relating potential pile tip damage to cone tip resistance from Cone Penetration Tests (CPTs) has been proposed in the literature. Gaussian processes are powerful stochastic models that enable probabilistic spatial interpolation of soil data at any location within a site. On this basis, this study utilizes sparse CPT data from a site in the North Sea, to first develop an efficient Gaussian process regression model, which is used to derive a three-dimensional (3D) probabilistic predictive map of the cone tip resistance. Assuming deterministic loading conditions and a factual collision with a boulder of pre-defined properties, the cone tip resistance predictive model is subsequently used for a probabilisticTip damage of monopiles from boulder collisions during installation has emerged as a critical design issue, primarily due to the combination of the widespread use of large-diameter piles and the complexity of the ground conditions at the available sites. Recently, a framework relating potential pile tip damage to cone tip resistance from Cone Penetration Tests (CPTs) has been proposed in the literature. Gaussian processes are powerful stochastic models that enable probabilistic spatial interpolation of soil data at any location within a site. On this basis, this study utilizes sparse CPT data from a site in the North Sea, to first develop an efficient Gaussian process regression model, which is used to derive a three-dimensional (3D) probabilistic predictive map of the cone tip resistance. Assuming deterministic loading conditions and a factual collision with a boulder of pre-defined properties, the cone tip resistance predictive model is subsequently used for a probabilistic preliminary assessment of potential pile tip damage. Results of the analysis are realistic 3D probability maps of potential damage that aim to support engineering judgment and contribute towards cost-effective site investigation planning and offshore wind farm design.zeige mehrzeige weniger

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Metadaten
Autor*innen:Orestis Zinas, Iason Papaioannou, Ronald Schneider, Pablo CuéllarORCiD, Matthias Baeßler
Dokumenttyp:Beitrag zu einem Tagungsband
Veröffentlichungsform:Graue Literatur
Sprache:Englisch
Titel des übergeordneten Werkes (Englisch):Proceedings of the fifth International Symposium on Frontiers in Offshore Geotechnics (ISFOG 2025)
Jahr der Erstveröffentlichung:2025
Organisationseinheit der BAM:7 Bauwerkssicherheit
7 Bauwerkssicherheit / 7.2 Ingenieurbau
Veröffentlichende Institution:Bundesanstalt für Materialforschung und -prüfung (BAM)
Verlag:International Society for Soil Mechanics and Geotechnical Engineering
Verlagsort:London
Erste Seite:505
Letzte Seite:510
DDC-Klassifikation:Technik, Medizin, angewandte Wissenschaften / Ingenieurwissenschaften / Angewandte Physik
Freie Schlagwörter:Boulder impact; CPT data; Gaussian process regression; Preliminary pile tip damage assessment
Themenfelder/Aktivitätsfelder der BAM:Energie
Energie / Windenergie
Veranstaltung:5th International Symposium on Frontiers in Offshore Geotechnics (ISFOG 2025)
Veranstaltungsort:Nantes, France
Beginndatum der Veranstaltung:09.06.2025
Enddatum der Veranstaltung:13.06.2025
DOI:10.53243/ISFOG2025-323
URN:urn:nbn:de:kobv:b43-634417
ISBN:978-2-85782-758-0
Verfügbarkeit des Dokuments:Datei für die Öffentlichkeit verfügbar ("Open Access")
Lizenz (Deutsch):License LogoAllgemeines Deutsches Urheberrecht
Datum der Freischaltung:19.06.2025
Referierte Publikation:Nein
Schriftenreihen ohne Nummerierung:Wissenschaftliche Artikel der BAM
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