Rayleigh-Bénard对流中时空混沌的量化
Quantifying Spatiotemporal Chaos in Rayleigh-Bénard Convection
摘要：
利用大规模并行数值模拟，我们探讨了在实验相关的边界条件下，在圆柱形区域的Rayleigh-Bénard对流时空混沌。利用李雅普诺夫指数谱和首阶李雅普诺夫向量随系统参数的变化来量化流体对流中高维混沌的状态。我们探讨了李雅普诺夫指数谱的时间动力学与模式动力学之间的关系。对于混沌动力学，我们发现，所有的李雅普诺夫指数正相关的领先顺序李雅普诺夫指数，我们量化的细节，他们的动态响应的缺陷。的领导阶李雅普诺夫向量被用来识别的流体模式，显着贡献的混沌动力学的拓扑特征。我们的研究结果表明，从边界占主导地位的动力学散装占主导地位的动力学系统的大小增加。利用李雅普诺夫指数的谱计算分形维数随系统参数的变化，以量化潜在的高维奇异吸引子如何适应一系列不同的混沌动力学.
英文摘要：
Using large-scale parallel numerical simulations we explore spatiotemporal chaos in Rayleigh-Bénard convection in a cylindrical domain with experimentally relevant boundary conditions. We use the variation of the spectrum of Lyapunov exponents and the leading order Lyapunov vector with system parameters to quantify states of high-dimensional chaos in fluid convection. We explore the relationship between the time dynamics of the spectrum of Lyapunov exponents and the pattern dynamics. For chaotic dynamics we find that all of the Lyapunov exponents are positively correlated with the leading order Lyapunov exponent and we quantify the details of their response to the dynamics of defects. The leading order Lyapunov vector is used to identify topological features of the fluid patterns that contribute significantly to the chaotic dynamics. Our results show a transition from boundary dominated dynamics to bulk dominated dynamics as the system size is increased. The spectrum of Lyapunov exponents is used to compute the variation of the fractal dimension with system parameters to quantify how the underlying high-dimensional strange attractor accommodates a range of different chaotic dynamics.
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