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    Pacific Ocean Windspeeds Prediction by Gaidai Multivariate Risks Evaluation Method, Utilizing Self-Deconvolution

    Source: ASME Open Journal of Engineering:;2024:;volume( 003 )::page 31025-1
    Author:
    Gaidai, Oleg
    DOI: 10.1115/1.4066682
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The current study advances research on the consequences of global climate change by utilizing the novel Gaidai multivariate risks evaluation methodology to conduct spatiotemporal analysis of areal windspeeds. Multidimensional structural and environmental dynamic systems that have been either physically observed or numerically simulated over a representative time-lapse are particularly suitable for the Gaidai risks evaluation methodology. Current research also presents a novel non-parametric deconvolution extrapolation method. As this study has shown, given in situ environmental input, it is possible to accurately predict environmental system hazard risks, based even on a limited underlying dataset. Furthermore, because of their complex nonlinear cross-correlations between various environmental system-critical dimensions or components and large dimensionality, environmental dynamic systems are difficult to handle using traditional methods for evaluating risks. In the North Pacific, close to the Hawaiian Islands, NOAA buoys gathered raw in situ wind speed data, which has been utilized in the current study. Areal ocean wind speeds constitute quite a complex environmental dynamic system that is challenging to analyze because of its nonlinear, multidimensional, cross-correlated nature. Global warming had impacts on ocean windspeeds in the recent decade. Developing novel state-of-the-art environmental system risk evaluation methods is a principal component of modern offshore structural analysis in light of adverse weather. The advocated novel risk/hazard assessment approach may be used for resilient island cities design, especially those that are near ocean shore and hence exposed to extreme weather.
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      Pacific Ocean Windspeeds Prediction by Gaidai Multivariate Risks Evaluation Method, Utilizing Self-Deconvolution

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4305698
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    contributor authorGaidai, Oleg
    date accessioned2025-04-21T10:12:05Z
    date available2025-04-21T10:12:05Z
    date copyright10/11/2024 12:00:00 AM
    date issued2024
    identifier issn2770-3495
    identifier otheraoje_3_031025.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4305698
    description abstractThe current study advances research on the consequences of global climate change by utilizing the novel Gaidai multivariate risks evaluation methodology to conduct spatiotemporal analysis of areal windspeeds. Multidimensional structural and environmental dynamic systems that have been either physically observed or numerically simulated over a representative time-lapse are particularly suitable for the Gaidai risks evaluation methodology. Current research also presents a novel non-parametric deconvolution extrapolation method. As this study has shown, given in situ environmental input, it is possible to accurately predict environmental system hazard risks, based even on a limited underlying dataset. Furthermore, because of their complex nonlinear cross-correlations between various environmental system-critical dimensions or components and large dimensionality, environmental dynamic systems are difficult to handle using traditional methods for evaluating risks. In the North Pacific, close to the Hawaiian Islands, NOAA buoys gathered raw in situ wind speed data, which has been utilized in the current study. Areal ocean wind speeds constitute quite a complex environmental dynamic system that is challenging to analyze because of its nonlinear, multidimensional, cross-correlated nature. Global warming had impacts on ocean windspeeds in the recent decade. Developing novel state-of-the-art environmental system risk evaluation methods is a principal component of modern offshore structural analysis in light of adverse weather. The advocated novel risk/hazard assessment approach may be used for resilient island cities design, especially those that are near ocean shore and hence exposed to extreme weather.
    publisherThe American Society of Mechanical Engineers (ASME)
    titlePacific Ocean Windspeeds Prediction by Gaidai Multivariate Risks Evaluation Method, Utilizing Self-Deconvolution
    typeJournal Paper
    journal volume3
    journal titleASME Open Journal of Engineering
    identifier doi10.1115/1.4066682
    journal fristpage31025-1
    journal lastpage31025-8
    page8
    treeASME Open Journal of Engineering:;2024:;volume( 003 )
    contenttypeFulltext
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