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Modelling Thermally Induced Non-Equilibrium Gas Flows by Coupling Kinetic and Extended Thermodynamic Methods.
Yang, Weiqi; Gu, Xiao-Jun; Emerson, David R; Zhang, Yonghao; Tang, Shuo.
Afiliación
  • Yang W; School of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China.
  • Gu XJ; Scientific Computing Department, STFC Daresbury Laboratory, Warrington WA4 4AD, UK.
  • Emerson DR; James Weir Fluids Laboratory, Department of Mechanical and Aerospace Engineering, University of Strathclyde, Glasgow G1 1XJ, UK.
  • Zhang Y; Scientific Computing Department, STFC Daresbury Laboratory, Warrington WA4 4AD, UK.
  • Tang S; Scientific Computing Department, STFC Daresbury Laboratory, Warrington WA4 4AD, UK.
Entropy (Basel) ; 21(8)2019 Aug 20.
Article en En | MEDLINE | ID: mdl-33267529
ABSTRACT
Thermally induced non-equilibrium gas flows have been simulated in the present study by coupling kinetic and extended thermodynamic methods. Three different types of thermally induced gas flows, including temperature-discontinuity- and temperature-gradient-induced flows and radiometric flow, have been explored in the transition regime. The temperature-discontinuity-induced flow case has shown that as the Knudsen number increases, the regularised 26 (R26) moment equation system will gradually loss its accuracy and validation. A coupling macro- and microscopic approach is employed to overcome these problems. The R26 moment equations are used at the macroscopic level for the bulk flow region, while the kinetic equation associated with the discrete velocity method (DVM) is applied to describe the gas close to the wall at the microscopic level, which yields a hybrid DVM/R26 approach. The numerical results have shown that the hybrid DVM/R26 method can be faithfully used for the thermally induced non-equilibrium flows. The proposed scheme not only improves the accuracy of the results in comparison with the R26 equations, but also extends their capability with a wider range of Knudsen numbers. In addition, the hybrid scheme is able to reduce the computational memory and time cost compared to the DVM.
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Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Entropy (Basel) Año: 2019 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Entropy (Basel) Año: 2019 Tipo del documento: Article