Fragility and vulnerability development of offshore wind turbines under aero-hydro loadings

Cheng, Yusong; Luo, Yan; Wang, Jianze; Dai, Kaoshan; Wang, Wenze; Damatty, Ashraf El

doi:10.1016/j.engstruct.2023.116625

Cited by 3 publications

(1 citation statement)

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“…Commonly, the fragility of the blades and nacelle are interpolated from the fragility of the tower. For the nacelle, only three sources (Cheng et al, 2023;Dueñas-Osorio and Basu, 2008;Hemmati et al, 2019) directly and empirically derive the fragility of acceleration-sensitive nacelle components, such as the generator, inverter and control system.…”

Section: Resultsmentioning

confidence: 99%

Review article: Insuring the green economy against natural hazards – charting research frontiers in vulnerability assessment

Baskaran,

Ioannou,

Rossetto

et al. 2024

Preprint

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Abstract. The insurance of green economy assets against natural hazards is a growing market. This study explores whether currently available published knowledge is adequate for the vulnerability assessment of these assets to natural hazards. A matrix is constructed to demonstrate the vulnerability to functional loss of 37 asset classes in the renewable energy, green construction, resource management, carbon capture and storage, energy storage and sustainable transportation sectors. The 28 hazards adopted range from environmental and geophysical events to oceanic, coastal, and space weather events. A fundamental challenge in constructing the matrix was the lack of an asset-hazard taxonomy for the green economy. Each matrix cell represents the vulnerability of an asset to a specific hazard, based on a comprehensive systematic literature review. A confidence level is assigned to each vulnerability assessment based on a literature density heat map. The latter highlights specific knowledge gaps, and in particular a lack of quantitative vulnerability studies that appropriately represent all functional loss mechanisms in green economy assets. Apart from charting research gaps, a main output of this study is the proposal of a representative asset-hazard taxonomy to guide future, quantitative research that can be applied by the insurance industry.

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Section: Resultsmentioning

confidence: 99%