Gaidai-Xing reliability method validation for 10-MW floating wind turbines
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. T...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-05-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-33699-7 |
| _version_ | 1797811522084274176 |
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| author | Oleg Gaidai Yihan Xing Jingxiang Xu Rajiv Balakrishna |
| author_facet | Oleg Gaidai Yihan Xing Jingxiang Xu Rajiv Balakrishna |
| author_sort | Oleg Gaidai |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-13T07:24:57Z |
| format | Article |
| id | doaj.art-0b4d3a2e56984e34b54e45064901264b |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-13T07:24:57Z |
| publishDate | 2023-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-0b4d3a2e56984e34b54e45064901264b2023-06-04T11:25:46ZengNature PortfolioScientific Reports2045-23222023-05-0113111010.1038/s41598-023-33699-7Gaidai-Xing reliability method validation for 10-MW floating wind turbinesOleg Gaidai0Yihan Xing1Jingxiang Xu2Rajiv Balakrishna3Shanghai Ocean UniversityDepartment of Mechanical and Structural Engineering and Materials Science, University of StavangerShanghai Ocean UniversityDepartment of Mechanical and Structural Engineering and Materials Science, University of StavangerAbstract 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.https://doi.org/10.1038/s41598-023-33699-7 |
| spellingShingle | Oleg Gaidai Yihan Xing Jingxiang Xu Rajiv Balakrishna Gaidai-Xing reliability method validation for 10-MW floating wind turbines Scientific Reports |
| title | Gaidai-Xing reliability method validation for 10-MW floating wind turbines |
| title_full | Gaidai-Xing reliability method validation for 10-MW floating wind turbines |
| title_fullStr | Gaidai-Xing reliability method validation for 10-MW floating wind turbines |
| title_full_unstemmed | Gaidai-Xing reliability method validation for 10-MW floating wind turbines |
| title_short | Gaidai-Xing reliability method validation for 10-MW floating wind turbines |
| title_sort | gaidai xing reliability method validation for 10 mw floating wind turbines |
| url | https://doi.org/10.1038/s41598-023-33699-7 |
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