ArticleScientific reports2023
Gaidai-Xing reliability method validation for 10-MW floating wind turbines.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Future worldwide coronavirus disease 2019 epidemic predictions by Gaidai multivariate risk evaluation method.Analytical science advances · 2024Article
- Influenza-type epidemic risks by spatio-temporal Gaidai-Yakimov method.Dialogues in health · 2023Article
- Dementia death rates prediction.BMC psychiatry · 2023Article
- Gaidai-Xing reliability method validation for 10-MW floating wind turbines.Scientific reports · 2023Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In contrast to well-known bivariate statistical approach, which is known to properly forecast extreme response levels for two-dimensional systems, the research validates innovative structural reliability method, which is particularly appropriate for multi-dimensional structural responses. The disadvantage of dealing with large system dimensionality and cross-correlation across multiple dimensions is not a benefit of traditional dependability approaches that deal with time series. Since offshore constructions are built to handle extremely high wind and wave loads, understanding these severe stresses is essential, e.g. wind turbines should be built and operated with the least amount of inconvenience. In the first scenario, the blade root flapwise bending moment is examined, whereas in the second, the tower bottom fore-aft bending moment is examined. The FAST simulation program was utilized to generate the empirical bending moments for this investigation with the load instances activated at under-rated, rated, and above-rated speeds. The novel reliability approach, in contrast to conventional reliability methods, does not call for the study of a multi-dimensional reliability function in the case of numerical simulation. As demonstrated in this work, it is now possible to assess multi-degree-of-freedom nonlinear system failure probability, in the case when only limited system measurements are available.
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Registered trials
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