Computational modelling of hydrodynamic loads on offshore monopiles in concurrent wave and current conditions

UDC.coleccionInvestigación
UDC.departamentoConstrucións e Estruturas Arquitectónicas, Civís e Aeronáuticas
UDC.endPage15
UDC.grupoInvMecánica de Estruturas (ME)
UDC.institutoCentroCITEEC - Centro de Innovación Tecnolóxica en Edificación e Enxeñaría Civil
UDC.issue124204
UDC.journalTitleOcean Engineering
UDC.startPage1
UDC.volume352-2
dc.contributor.authorAl-Behadili, Ali Kareem Hilo
dc.contributor.authorNieto Mouronte, Félix
dc.contributor.authorBarajas, Gabriel
dc.contributor.authorLara, Javier L.
dc.contributor.authorAhn, Byoung-Kwon
dc.contributor.authorÁlvarez Naveira, Antonio José
dc.contributor.authorKozmar, Hrvoje
dc.date.accessioned2026-08-14T09:40:42Z
dc.date.available2026-08-14T09:40:42Z
dc.date.issued2026-04
dc.description.abstract[Abstract]: Offshore monopile wind-turbine systems face significant design challenges due to complex environmental loading conditions, including wind, waves, current, and their intricate coupling effects. Computational Fluid Dynamics (CFD) simulations of complex nonlinear wave-structure interactions have become essential for un-derstanding offshore systems. However, high-fidelity (HF) CFD analyses are computationally demanding, making it impractical to use them alone for extensive parametric studies. Surrogate models provide a promising alter-native, as they can deliver efficient and accurate predictions once trained. This study presents a methodology for combining HF computational models and a data-driven approach to assess hydrodynamic loads on an offshore monopile subjected to waves and current. A three-dimensional numerical wave tank was developed in the OpenFOAM environment and validated using experimental and theoretical data. This model accurately accounts for complex wave-current interactions and the resulting force variations on the monopile. The obtained results indicate that the hydrodynamic forces on the monopile are significantly affected when waves and current act concurrently. To reduce the extensive computational HF simulations, a Gaussian Process Regression (GPR)-based surrogate model was developed using HF simulations sampled via Latin Hypercube Sampling. The surrogate model was trained to predict peak inline and transverse forces for various wave heights, frequencies, and current velocities. The GPR model exhibits high accuracy with R²= 0.98 (coefficient of determination) and MAE = 0.03 (Mean Absolute Error) for the inline force, and R² = 0.94 and MAE = 0.01 for the transverse force, thus demonstrating its ability to accurately assess complex nonlinear responses, while reducing the computational demand significantly. These findings provide a practical and applicable solution for offshore structural design, especially during early-stage assessments or probabilistic load evaluations.
dc.description.sponsorshipThis research has been funded by the Marie Sklodowska-Curie Action call HORIZON-MSCA-2022-PF-01, grant agreement ID: 101108556, “FUNny-SUMO Fully Numerical strategy for Surrogate modeling of Monopile Offshore wind turbines”. Funding has been received from the Galician Regional Government Grant ED431C 2025/35. This work was supported by the Croatian Science Foundation under the project number HRZZ-IP-2022-10-9434. This paper has been funded by the European Union (NextGenerationEU) under the National Recovery and Resilience Plan 2021–2026 (NRRP), through the UNIZAG FSB institutional project “Structural aerodynamics”, approved by the Ministry of Science, Education and Youth of the Republic of Croatia (component C3.2, source 581). This research project was made possible through the access granted by the Galician Supercomputing Center (CESGA) to its FinisTerrae III supercomputer, funded by the NextGeneration EU Recovery, Transformation and Resilience Plan and the European Regional Development Fund (ERDF).
dc.description.sponsorshipXunta de Galicia; ED431C 2025/35
dc.description.sponsorshipCroatia. Croatian Science Foundation; HRZZ-IP-2022-10-9434
dc.identifier.citationHilo, A. K., Nieto, F., Barajas, G., Lara, J. L., Ahn, B. K., Alvarez, A. J., & Kozmar, H. (2026). Computational modelling of hydrodynamic loads on offshore monopiles in concurrent wave and current conditions. Ocean engineering, 352, 124204. https://doi.org/10.1016/j.oceaneng.2026.124204
dc.identifier.doi10.1016/j.oceaneng.2026.124204
dc.identifier.issn1873-5258
dc.identifier.issn0029-8018
dc.identifier.urihttps://hdl.handle.net/2183/49028
dc.language.isoeng
dc.publisherElsevier
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/HE/101108556
dc.relation.urihttps://doi.org/10.1016/j.oceaneng.2026.124204
dc.rightsAttribution 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectComputational fluid dynamics
dc.subjectSurrogate model
dc.subjectGaussian process regression
dc.subjectOffshore monopile
dc.subjectWave
dc.subjectCurrent
dc.subjectHydrodynamic forces
dc.titleComputational modelling of hydrodynamic loads on offshore monopiles in concurrent wave and current conditions
dc.typejournal article
dc.type.hasVersionVoR
dspace.entity.typePublication
relation.isAuthorOfPublication3fed60ab-c291-40ea-85bf-c77bead0756b
relation.isAuthorOfPublication5aac114c-b4de-4465-a6b8-2c65324366a9
relation.isAuthorOfPublication74c1b663-1675-4374-a367-024120d8a8ee
relation.isAuthorOfPublication.latestForDiscovery3fed60ab-c291-40ea-85bf-c77bead0756b

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