熱対流系セルパターンのモード遷移確率制御に関する数値実験

抄録

In a thermal convection field constrained by right and left insulated walls, stable multiple solutions easily exist. In the case of a two-dimensional cavity with aspect ratio of 1.5, whose upper wall is cooled and lower wall is heated at a constant temperature, the two modes of thermal convection cell pattern are stable at Rayleigh number Ra of 2.0 × 10⁵. That is, one-cell-mode and two-cell-mode. However, as Ra increases to 3.5 × 10⁵, both modes become unstable, and appear in similar probability. The objective of this work is to demonstrate the possibility of controlling convection patterns under unstable conditions. We found that estimation using artificial neural network is effective to increase the probability of obtaining a desired mode, even in the slightly higher Ra of 2.5×10⁵.