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Numerical solution of optimal magnetic suppression of natural convection in magneto-hydrodynamic flows by empirical reduction of modes

机译:基于模态经验折减法的磁流体动力流自然对流最优磁抑制数值解

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摘要

The control of natural convection in magneto-hydrodynamic (MHD) flow is investigated by means of the Karhunen-Loeve Galerkin procedure [Int J Numer Meth Engng 1998;41:1133-51]. The Karhunen-Loeve Galerkin procedure, which is a type of Galerkin methods that employs the empirical eigenfunctions of the Karhunen-Loeve decomposition as basis functions, can reduce non-linear partial differential equations to sets of minimal number of ordinary differential equations by limiting the solution space to the smallest linear subspace that is sufficient to describe the observed phenomena. In the present investigation, it is demonstrated that the Karhunen-Loeve Galerkin procedure is well suited for the problems of control or optimization, where one has to solve the governing equations repeatedly but one can also estimate the approximate solution space from the range of control variable. The performance of the Karhunen-Loeve Galerkin procedure for solving the optimal control problem of natural convection is assessed in comparison with the traditional technique employing the Boussinesq equation, and is found to be very accurate as well as efficient.
机译:利用Karhunen-Loeve Galerkin程序[Int J Numer Meth Engng 1998; 41:1133-51]研究了磁流体动力学(MHD)流动中自然对流的控制。 Karhunen-Loeve Galerkin过程是将Karhunen-Loeve分解的经验特征函数用作基函数的一种Galerkin方法,可以通过限制解将非线性偏微分方程简化为最小数量的常微分方程组。空间到最小的线性子空间,足以描述观察到的现象。在本研究中,证明了Karhunen-Loeve Galerkin程序非常适合控制或优化问题,在这种情况下,人们必须反复求解控制方程,但也可以从控制变量的范围估计近似解空间。 。与采用Boussinesq方程的传统技术相比,评估了Karhunen-Loeve Galerkin过程解决自然对流最优控制问题的性能,发现该方法非常准确且有效。

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