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Multi-purpose floating platforms are emerging as a promising concept in ocean engineering applications, thanks to their capability of ensuring system integration, cost reduction and modularization. However, their increasing complexity requires the development of numerical tools, which need to be validated experimentally through adequate physical models. New challenges hence arise, since the subsystems integrated in the structure generally follow different scaling laws and may need relatively large physical models to achieve a reliable similitude between the full-scale structure and its physical model counterpart. The latter issue can be critical, because indoor tests in wave tanks and basins constrain the scale factors to the size of the available facilities. Open-sea experiments, albeit challenging because of the uncontrolled environmental conditions, could be a valid complement to the traditional indoor tests. This article proposes a review of the multi-physics scaling strategies for the subsystems usually embedded in multi-purpose floating platforms, i.e. floating support, mooring system, wind turbine, wave energy converter and aquaculture facilities, by providing a critical analysis on the relevance of the scaling factor and of the scaling strategy. The paper may also serve as a guide for practical applications involving one or several of the considered subsystems.
Physical models, Offshore wind turbines, Froude scaling of floating structures, Multi-purpose floating structures, VM, Naval architecture. Shipbuilding. Marine engineering, H2020, Floating wave energy converters, Floating fish net cages, 620, The Blue Growth Farm, BGF
Physical models, Offshore wind turbines, Froude scaling of floating structures, Multi-purpose floating structures, VM, Naval architecture. Shipbuilding. Marine engineering, H2020, Floating wave energy converters, Floating fish net cages, 620, The Blue Growth Farm, BGF
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 40 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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