{"title":"基于聚类的风力机尾流概率结构动力学模型","authors":"N. Ali, M. Calaf, R. B. Cal","doi":"10.1080/14685248.2021.1925125","DOIUrl":null,"url":null,"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.","PeriodicalId":49967,"journal":{"name":"Journal of Turbulence","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2021-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/14685248.2021.1925125","citationCount":"7","resultStr":"{\"title\":\"Cluster-based probabilistic structure dynamical model of wind turbine wake\",\"authors\":\"N. Ali, M. Calaf, R. B. Cal\",\"doi\":\"10.1080/14685248.2021.1925125\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":49967,\"journal\":{\"name\":\"Journal of Turbulence\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2021-05-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/14685248.2021.1925125\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Turbulence\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1080/14685248.2021.1925125\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MECHANICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Turbulence","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/14685248.2021.1925125","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MECHANICS","Score":null,"Total":0}
Cluster-based probabilistic structure dynamical model of wind turbine wake
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.
期刊介绍:
Turbulence is a physical phenomenon occurring in most fluid flows, and is a major research topic at the cutting edge of science and technology. Journal of Turbulence ( JoT) is a digital forum for disseminating new theoretical, numerical and experimental knowledge aimed at understanding, predicting and controlling fluid turbulence.
JoT provides a common venue for communicating advances of fundamental and applied character across the many disciplines in which turbulence plays a vital role. Examples include turbulence arising in engineering fluid dynamics (aerodynamics and hydrodynamics, particulate and multi-phase flows, acoustics, hydraulics, combustion, aeroelasticity, transitional flows, turbo-machinery, heat transfer), geophysical fluid dynamics (environmental flows, oceanography, meteorology), in physics (magnetohydrodynamics and fusion, astrophysics, cryogenic and quantum fluids), and mathematics (turbulence from PDE’s, model systems). The multimedia capabilities offered by this electronic journal (including free colour images and video movies), provide a unique opportunity for disseminating turbulence research in visually impressive ways.