The Interaction of Ocean Waves and Offshore Structures

Dear Colleagues,

A vast variety of offshore structures are employed to explore, produce, and transport offshore resources, to carry people and products across the oceans, and for nations to defend themselves. Of central importance for their design is the reliable prediction of forces associated with the interaction of ocean waves and these structures. This requires understanding not only the physics of flow separation and turbulence, but also a competent usage of computational fluid dynamics. Although offshore structures have recently demonstrated importance for the production of oil and gas, these structures are increasingly utilized to support wind turbines and wave energy devices. Offshore structures are exposed to the harsh environment of waves, current, wind, and possibly even earthquakes. As the influence of the environmental forces is random, their design must be based on the extreme responses during the structure’s lifetime.

This Special Issue aims to collect papers that present research advances related to all aspects concerned with the interaction of ocean waves and offshore structures. It is known that the safe and economic design of offshore structures is complex, requiring a thorough understanding of the harsh environmental forces acting on these structures. Major difficulties are associated with the three-dimensional and random nature of the seaway-induced forces and the effects of turbulence. Indeed, a satisfying closure model for turbulence is still not available. Current progress demonstrated that RANS closure models remain an essential element of applied CFD techniques, and hybrid simulations are expanding to improve the accuracy of space and time fluctuations that are not available from pure RANS solutions. The extraordinary success of machine learning (ML) led to transformative advances in the area of turbulence closure modeling. However, progress toward accurate and predictive ML-RANS closure models is slow. A more complete comprehension of the complex turbulence phenomenon is necessary to employ ML techniques that are inconsistent with turbulence physics. Nevertheless, as ML methods evolve and our understanding of the turbulence phenomenon improves, turbulence closure modeling using machine learning is an opportunity for growth and change.

Prof. Dr. Bettar Ould el Moctar
Dr. Thomas Schellin
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• wave modeling
• wave-induced loads and motions
• offshore structures
• computational methods for offshore structures
• fluid-offshore structure interaction