Abstract
Large-scale offshore wind farms have emerged as a critical renewable energy technology to reduce greenhouse gas (GHG) emission and autonomy in energy production. Each of these wind farms consists of many wind turbine generators (WTG) mounted on a support structure and is capable of generating up to (as we write the paper) 1.2 GW of power. These are relatively new technological advancements which are installed in harsh offshore environments. Naturally, the design of foundations for such structures is challenging. Furthermore, WTG support structures due to its shape and form (heavy rotating mass at the top of a slender tower) are dynamically sensitive in the sense that the natural frequency of such system is very close to the forcing frequencies acting on them. The aims of this keynote lecture are as follows: (a) summarise the loads acting on the structure together with its associated complexity; (b) discuss the challenges in designing such foundations; (c) describe the rationale behind scaled models tests that supported the development of offshore wind turbine design philosophy; (d) draw parallel with other geotechnical scaled model tests and discuss the scaling issues; (e) propose a method to scale the model tests for predicting prototype consequences. While there is no track record of long-term performances of these new structures, design and construction of these must be carried out for 25–30 years and it is argued that scaled model tests are necessary. Finally, the lecture concludes that well thought out scaled models tests can be effective in predicting the long-term issues and engineers need to learn from other disciplines.
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The first author would like to thank the support from EPSRC, RWE Innogy, VJ Tech for carrying out the research.
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Bhattacharya, S., Nikitas, G., Jalbi, S. (2018). On the Use of Scaled Model Tests for Analysis and Design of Offshore Wind Turbines. In: Krishna, A., Dey, A., Sreedeep, S. (eds) Geotechnics for Natural and Engineered Sustainable Technologies. Developments in Geotechnical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-10-7721-0_6
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