The Richtmyer-Meshkov Instability Impacted by the Interface with Different Components Distribution

Authors: Sheng-Bo Zhang, Huan-Hao Zhang, Zhi-Hua Chen, Chun Zheng

Abstract:

In this paper, the Richtmyer-Meshkov instability has been studied numerically by using the high-resolution Roe scheme based on the two-dimensional unsteady Euler equation, which was caused by the interaction between shock wave and the helium circular light gas cylinder with different component distributions. The numerical results further discuss the deformation process of the gas cylinder, the wave structure of the flow field and quantitatively analyze the characteristic dimensions (length, height, and central axial width) of the gas cylinder, the volume compression ratio of the cylinder over time. In addition, the flow mechanism of shock-driven interface gas mixing is analyzed from multiple perspectives by combining it with the flow field pressure, velocity, circulation, and gas mixing rate. Then the effects of different initial component distribution conditions on interface instability are investigated. The results show when the diffusion interface transit to the sharp interface, the reflection coefficient gradually increases on both sides of the interface. When the incident shock wave interacts with the cylinder, the transmission of the shock wave will transit from conventional transmission to unconventional transmission. At the same time, the reflected shock wave is gradually strengthened, and the transmitted shock wave is gradually weakened, which leads to an increase in the Richtmyer-Meshkov instability. Moreover, the Atwood number on both sides of the interface also increases as the diffusion interface transit to the sharp interface, which leads to an increase in the Rayleigh-Taylor instability and the Kelvin-Helmholtz instability. Therefore, the increase in instability will lead to an increase the circulation, resulting in an increase in the growth rate of gas mixing rate.

Keywords: shock wave, He light cylinder, Richtmyer-Meshkov instability, Gaussian distribution