A Computational Investigation of Dynamic Stabilization of Rayleigh-Bénard Convection Under System Acceleration

The static and dynamic stability of Rayleigh-Bénard convection in a rectangular flow domain is computationally investigated. Sinusoidal vertical oscillations are applied to the system to provide dynamic flow stabilization. Stability maps are produced for a range of flow and heating conditions, and are compared to experimental measurements and linear stability analysis predictions from existing literature. Density variation is introduced through: 1) the Boussinesq approximation, 2) a linearly varying temperature dependent equation of state (EOS) and 3) the perfect gas EOS. Significant effects of choice of EOS on dynamic stability are observed. These weakly compressible flows are solved efficiently using an implicit numerical method that has been developed to solve the momentum, continuity, enthalpy and state equations simultaneously in fully coupled fashion. This block coupled system of equations is linearized with Newton’s method, and quadratic convergence is achieved. The details of these numerics are presented.

© 2020, ASME. Originally published in the ASME 2020 Heat Transfer Summer Conference.

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Work Title A Computational Investigation of Dynamic Stabilization of Rayleigh-Bénard Convection Under System Acceleration
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Open Access
Creators
  1. Ilker Topcuoglu
  2. Robert F. Kunz
  3. Robert W. Smith
License CC BY 4.0 (Attribution)
Work Type Article
Publisher
  1. American Society of Mechanical Engineers
Publication Date July 13, 2020
Publisher Identifier (DOI)
  1. 10.1115/ht2020-9020
Source
  1. ASME 2020 Heat Transfer Summer Conference
Deposited April 25, 2022

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  • Added Creator Robert F. Kunz
  • Added Creator Robert W. Smith
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  • Updated Work Title, Description Show Changes
    Work Title
    • A COMPUTATIONAL INVESTIGATION OF DYNAMIC STABILIZATION OF RAYLEIGH-BE´NARD CONVECTION UNDER SYSTEM ACCELERATION
    • A Computational Investigation of Dynamic Stabilization of Rayleigh-Bénard Convection Under System Acceleration
    Description
    • <jats:title>Abstract</jats:title>
    • <jats:p>The static and dynamic stability of Rayleigh-Bénard convection in a rectangular flow domain is computationally investigated. Sinusoidal vertical oscillations are applied to the system to provide dynamic flow stabilization. Stability maps are produced for a range of flow and heating conditions, and are compared to experimental measurements and linear stability analysis predictions from existing literature. Density variation is introduced through: 1) the Boussinesq approximation, 2) a linearly varying temperature dependent equation of state (EOS) and 3) the perfect gas EOS. Significant effects of choice of EOS on dynamic stability are observed. These weakly compressible flows are solved efficiently using an implicit numerical method that has been developed to solve the momentum, continuity, enthalpy and state equations simultaneously in fully coupled fashion. This block coupled system of equations is linearized with Newton’s method, and quadratic convergence is achieved. The details of these numerics are presented.</jats:p>
    • The static and dynamic stability of Rayleigh-Bénard convection in a rectangular flow domain is computationally investigated. Sinusoidal vertical oscillations are applied to the system to provide dynamic flow stabilization. Stability maps are produced for a range of flow and heating conditions, and are compared to experimental measurements and linear stability analysis predictions from existing literature. Density variation is introduced through: 1) the Boussinesq approximation, 2) a linearly varying temperature dependent equation of state (EOS) and 3) the perfect gas EOS. Significant effects of choice of EOS on dynamic stability are observed. These weakly compressible flows are solved efficiently using an implicit numerical method that has been developed to solve the momentum, continuity, enthalpy and state equations simultaneously in fully coupled fashion. This block coupled system of equations is linearized with Newton’s method, and quadratic convergence is achieved. The details of these numerics are presented.
  • Updated