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    Fast Prediction Method for Steady-State Heat Convection

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    Type
    Article
    Authors
    Wáng, Yì
    Yu, Bo
    Sun, Shuyu cc
    KAUST Department
    Computational Transport Phenomena Lab
    Earth Science and Engineering Program
    Environmental Science and Engineering Program
    Physical Science and Engineering (PSE) Division
    Date
    2012-03-14
    Online Publication Date
    2012-03-14
    Print Publication Date
    2012-04
    Permanent link to this record
    http://hdl.handle.net/10754/562128
    
    Metadata
    Show full item record
    Abstract
    A reduced model by proper orthogonal decomposition (POD) and Galerkin projection methods for steady-state heat convection is established on a nonuniform grid. It was verified by thousands of examples that the results are in good agreement with the results obtained from the finite volume method. This model can also predict the cases where model parameters far exceed the sample scope. Moreover, the calculation time needed by the model is much shorter than that needed for the finite volume method. Thus, the nonuniform POD-Galerkin projection method exhibits high accuracy, good suitability, and fast computation. It has universal significance for accurate and fast prediction. Also, the methodology can be applied to more complex modeling in chemical engineering and technology, such as reaction and turbulence. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
    Citation
    Wang, Y., Yu, B., & Sun, S. (2012). Fast Prediction Method for Steady-State Heat Convection. Chemical Engineering & Technology, 35(4), 668–678. doi:10.1002/ceat.201100428
    Sponsors
    The study is supported by the National Natural Science Foundation of China (No. 51176204 and No. 51134006), and the State Key Laboratory of Multiphase Flow in Power Engineering (Xi'an Jiaotong University).
    Publisher
    Wiley
    Journal
    Chemical Engineering & Technology
    DOI
    10.1002/ceat.201100428
    ae974a485f413a2113503eed53cd6c53
    10.1002/ceat.201100428
    Scopus Count
    Collections
    Articles; Environmental Science and Engineering Program; Physical Science and Engineering (PSE) Division; Earth Science and Engineering Program; Computational Transport Phenomena Lab

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