Multivariate ocean waves dynamics in North Sea and Norwegian Sea by Gaidai reliability method

Current study presents state-of-the-art approach for evaluating spatiotemporal multivariate environmental risks, especially suitable for complex environmental systems that have been either numerically simulated or physically observed. Advocated methodology provides accurate hazard risk forecasts, based on real-time in situ environmental data. Design of offshore structures requires multivariate risk assessment – offshore and naval operations require both short- and long-term risk and reliability analyses. Contemporary risk evaluation techniques often struggle with raw timeseries multivariate data due to intrinsic multidimensionality and nonlinear interconnections among critical system’s dimensions/components. In the current study effectiveness of the Gaidai multivariate risk evaluation method is illustrated by utilizing significant wave heights dataset, measured within two offshore zones: Heidrun and Troll Norwegian oil fields. Analyzing offshore waves being particularly challenging due to their complexity, high nonlinearity, multidimensionality, yet dynamic inter-correlations. Global warming being among several significant factors, affecting ocean and sea wave heights. For naval, offshore and marine structures operating in harsh weather conditions, robust multivariate environmental risk evaluation methods being crucial for both design and safe operations. Current study aims to validate and benchmark state-of-the-art methodology, enabling extraction. Advocated approach allows for efficient yet accurate assessment of global damages, failures or hazard risks for a wide range of complex nonlinear multivariate environmental and energy systems. Primary advantage of presented multivariate reliability methodology lies within its ability to treat complex systems with practically unlimited number of dimensions, while existing reliability methods being mostly limited to univariate and bivariate analyses.

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Publication Details

Journal
Energy Reports
Published
2024-08-23
DOI
https://doi.org/10.1016/j.egyr.2024.08.040
Citations
44
Primary Topic
Ocean Waves and Remote Sensing
Type
article
Field-Weighted Citation Impact
21.15
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article

Multivariate ocean waves dynamics in North Sea and Norwegian Sea by Gaidai reliability method

Yu Cao, Oleg Gaidai, Hongchen Li, Yan Zhu et al.
44 citations
Energy Reports
Ocean Waves and Remote Sensing
21.15
article

Multivariate ocean waves dynamics in North Sea and Norwegian Sea by Gaidai reliability method

Yu Cao, Oleg Gaidai, Hongchen Li, Yan Zhu, Zirui Liu, Jinlu Sheng, Alia Ashraf
article en
44 citations

Abstract

Current study presents state-of-the-art approach for evaluating spatiotemporal multivariate environmental risks, especially suitable for complex environmental systems that have been either numerically simulated or physically observed. Advocated methodology provides accurate hazard risk forecasts, based on real-time in situ environmental data. Design of offshore structures requires multivariate risk assessment – offshore and naval operations require both short- and long-term risk and reliability analyses. Contemporary risk evaluation techniques often struggle with raw timeseries multivariate data due to intrinsic multidimensionality and nonlinear interconnections among critical system’s dimensions/components. In the current study effectiveness of the Gaidai multivariate risk evaluation method is illustrated by utilizing significant wave heights dataset, measured within two offshore zones: Heidrun and Troll Norwegian oil fields. Analyzing offshore waves being particularly challenging due to their complexity, high nonlinearity, multidimensionality, yet dynamic inter-correlations. Global warming being among several significant factors, affecting ocean and sea wave heights. For naval, offshore and marine structures operating in harsh weather conditions, robust multivariate environmental risk evaluation methods being crucial for both design and safe operations. Current study aims to validate and benchmark state-of-the-art methodology, enabling extraction. Advocated approach allows for efficient yet accurate assessment of global damages, failures or hazard risks for a wide range of complex nonlinear multivariate environmental and energy systems. Primary advantage of presented multivariate reliability methodology lies within its ability to treat complex systems with practically unlimited number of dimensions, while existing reliability methods being mostly limited to univariate and bivariate analyses.

Energy ReportsVol. 12
Jiangsu University of Science and Technology (CN), Shanghai Ocean University (CN), Chongqing Jiaotong University (CN)
Life below water
Openalex Percentile: Top 0%
Ocean Waves and Remote Sensing
21.15
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