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Magnetically Induced Rotating Rayleigh-Taylor Instability
Published on: March 3, 2017
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Lattice Boltzmann simulation of three-dimensional Rayleigh-Taylor instability
1Department of Physics, Hangzhou Dianzi University - Hangzhou 310018, China.
Physical Review. E
|April 15, 2016
Summary
This study explores the 3D Rayleigh-Taylor instability (RTI) in a square duct using a lattice Boltzmann model. Higher Reynolds numbers lead to chaotic interface dynamics, while lower numbers result in smoother interfaces and constant bubble velocity.
Area of Science:
- Fluid Dynamics
- Computational Physics
- Multiphase Flow
Background:
- The Rayleigh-Taylor instability (RTI) is a fundamental phenomenon in fluid dynamics.
- Understanding RTI is crucial for various applications, including inertial confinement fusion and astrophysical processes.
- Previous studies have primarily focused on 2D simulations or higher Atwood numbers.
Purpose of the Study:
- To investigate the three-dimensional Rayleigh-Taylor instability (RTI) in a square duct with a low Atwood number (A(t)=0.15).
- To analyze the effect of Reynolds number on interfacial dynamics, bubble, and spike amplitudes.
- To explore the late-time behavior and topological structures of the RTI.
Main Methods:
- Utilized a multiple-relaxation-time lattice Boltzmann (LB) multiphase model for 3D simulations.
- Investigated a long square duct geometry (12W × W × W).
- Employed Graphics Processing Unit (GPU) parallel computing to handle computational costs.
Main Results:
- At high Reynolds numbers, RTI exhibits distinct stages: linear growth, terminal velocity, reacceleration, and chaotic development.
- Complex interface topologies and dissociative drops were observed at late stages.
- Bubble and spike velocities exceeded potential flow theory predictions, with normalized acceleration fluctuating around 0.16.
- At low Reynolds numbers, later stages were not reached, interfaces remained smooth, and bubble velocity approached a constant, aligning with extended Layzer and modified potential theories.
Conclusions:
- Reynolds number significantly influences the progression and complexity of 3D RTI.
- The LB model accurately captures the transition from ordered to chaotic interfacial dynamics.
- Simulation results provide valuable data for validating theoretical models of RTI at low Atwood numbers.
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