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Cluster-based probabilistic structure dynamical model of wind turbine wake.

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Title: Cluster-based probabilistic structure dynamical model of wind turbine wake.
Authors: Ali, Naseem1 (AUTHOR) rcal@pdx.edu, Calaf, Marc2 (AUTHOR), Cal, Raúl Bayoán1 (AUTHOR) rcal@pdx.edu
Source: Journal of Turbulence. Aug2021, Vol. 22 Issue 8, p497-516. 20p.
Subjects: Proper orthogonal decomposition, Distribution (Probability theory), Dynamical systems, Cluster analysis (Statistics), Group velocity, Wind turbines
Abstract: For complex flow systems like the one of the wind turbine wakes, which include a range of interacting turbulent scales, there is the potential to reduce the high dimensionality of the problem to low-rank approximations. Unsupervised cluster analysis based on the proper orthogonal decomposition is used here to identify the coherent structure and transition dynamics of wind turbine wake. Through the clustering approach, the nonlinear dynamics of the turbine wake is presented in a linear framework. The features of the fluctuating velocity are grouped based on similarity and presented as the centroids of the defining clusters. Determined from probability distribution of the transition, the dynamical system identifies the features of the wakes and the inherent dynamics of the flow. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Turbulence is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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Header DbId: egs
DbLabel: Engineering Source
An: 151609784
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Cluster-based probabilistic structure dynamical model of wind turbine wake.
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  Data: <searchLink fieldCode="AR" term="%22Ali%2C+Naseem%22">Ali, Naseem</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> rcal@pdx.edu</i><br /><searchLink fieldCode="AR" term="%22Calaf%2C+Marc%22">Calaf, Marc</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cal%2C+Raúl+Bayoán%22">Cal, Raúl Bayoán</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> rcal@pdx.edu</i>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Turbulence%22">Journal of Turbulence</searchLink>. Aug2021, Vol. 22 Issue 8, p497-516. 20p.
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  Data: <searchLink fieldCode="DE" term="%22Proper+orthogonal+decomposition%22">Proper orthogonal decomposition</searchLink><br /><searchLink fieldCode="DE" term="%22Distribution+%28Probability+theory%29%22">Distribution (Probability theory)</searchLink><br /><searchLink fieldCode="DE" term="%22Dynamical+systems%22">Dynamical systems</searchLink><br /><searchLink fieldCode="DE" term="%22Cluster+analysis+%28Statistics%29%22">Cluster analysis (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Group+velocity%22">Group velocity</searchLink><br /><searchLink fieldCode="DE" term="%22Wind+turbines%22">Wind turbines</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: For complex flow systems like the one of the wind turbine wakes, which include a range of interacting turbulent scales, there is the potential to reduce the high dimensionality of the problem to low-rank approximations. Unsupervised cluster analysis based on the proper orthogonal decomposition is used here to identify the coherent structure and transition dynamics of wind turbine wake. Through the clustering approach, the nonlinear dynamics of the turbine wake is presented in a linear framework. The features of the fluctuating velocity are grouped based on similarity and presented as the centroids of the defining clusters. Determined from probability distribution of the transition, the dynamical system identifies the features of the wakes and the inherent dynamics of the flow. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Turbulence is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/14685248.2021.1925125
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 20
        StartPage: 497
    Subjects:
      – SubjectFull: Proper orthogonal decomposition
        Type: general
      – SubjectFull: Distribution (Probability theory)
        Type: general
      – SubjectFull: Dynamical systems
        Type: general
      – SubjectFull: Cluster analysis (Statistics)
        Type: general
      – SubjectFull: Group velocity
        Type: general
      – SubjectFull: Wind turbines
        Type: general
    Titles:
      – TitleFull: Cluster-based probabilistic structure dynamical model of wind turbine wake.
        Type: main
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      – PersonEntity:
          Name:
            NameFull: Ali, Naseem
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          Name:
            NameFull: Calaf, Marc
      – PersonEntity:
          Name:
            NameFull: Cal, Raúl Bayoán
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          Dates:
            – D: 01
              M: 08
              Text: Aug2021
              Type: published
              Y: 2021
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              Value: 14685248
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              Value: 22
            – Type: issue
              Value: 8
          Titles:
            – TitleFull: Journal of Turbulence
              Type: main
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