機械学習を用いた平面クエット乱流における低次元力学系の構築

抄録

In a dissipative system, there exists the (global) attractor which has finite fractal dimensions. The flow on the attractor can be parametrized by a finite number of parameters (Temmam 1987). For low-Reynolds-number turbulence in plane Couette flow, we construct precise low-dimensional governing equations on the attractors using machine learning.