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首页> 外文期刊>Computers & mathematics with applications >Predictor-Corrector Nodal Integral Method for simulation of high Reynolds number fluid flow using larger time steps in Burgers' equation
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Predictor-Corrector Nodal Integral Method for simulation of high Reynolds number fluid flow using larger time steps in Burgers' equation

机译:使用Burgers方程中较大的时间步长模拟高雷诺数流体流动的Predictor-Corrector节点积分方法

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摘要

Nodal Integral Methods (NIM), although frequently used for solving neutron transport equations, have not found wider acceptance for solving fluid flow problems. One of the pivotal reasons behind this is the lack of efficient non-linear solvers for the system of coupled algebraic equations obtained by these methods, thus making such methods prohibitively expensive for highly nonlinear (higher Reynolds number) fluid flow problems. Successive improvements in earlier attempts resulted in an improved version called Modified NIM (MNIM) scheme; following which, a further modified version appeared (called as (MNIM)-N-2), that used the concept of the delayed coefficients. Upon comparing the solutions obtained using MNIM and (MNIM)-N-2 schemes, respectively, it was observed that although the modified scheme with delayed coefficients ((MNIM)-N-2) has significantly faster convergence, it is less accurate. The convergence and accuracy are very likely to suffer to a significant extent in the high Reynolds number fluid flows, especially when a large time-step is to be considered. In order to resolve these difficulties, a new type of physics-based predictor-corrector algorithm is proposed in the present study. In the proposed computational algorithm, the linearized (MNIM)-N-2 scheme is used to predict the solution, whereas the MNIM scheme is utilized to improve the predictive guess. The novelty of such a hybrid numerical algorithm comes from the fact that it combines the advantage of the faster convergence of (MNIM)-N-2 with the accuracy of the MNIM scheme. The algorithm also benefits from the unique inclusion of Jacobian-free Newton-Krylov (JFNK) method, which helps in getting rid of the formation of large Jacobian matrices, thereby reducing unnecessary computational overhead. The proposed methodology has been applied to solve a non-linear convection-diffusion problem, represented by the Burgers' equation. The computational results for both one-dimensional and two-dimensional Burgers' equation are presented to demonstrate the effectiveness of the developed novel algorithm, as well as, the advantage it offers over the existing numerical methods. (C) 2019 Elsevier Ltd. All rights reserved.
机译:节点积分方法(NIM)尽管经常用于求解中子输运方程,但并未找到更广泛的解决流体流动问题的方法。其背后的关键原因之一是,对于通过这些方法获得的耦合代数方程组的系统缺乏有效的非线性求解器,因此,对于高度非线性(较高的雷诺数)的流体流动问题,此类方法的成本过高。早期尝试的不断改进导致了改进版本,称为改良NIM(MNIM)方案。随后,出现了进一步的修改版本(称为(MNIM)-N-2),该版本使用了延迟系数的概念。通过分别比较使用MNIM和(MNIM)-N-2方案获得的解决方案,可以观察到,尽管具有延迟系数的改进方案((MNIM)-N-2)收敛速度明显加快,但准确性较低。在高雷诺数流体流动中,收敛性和准确性很可能会在很大程度上受到影响,尤其是在考虑较长时间步长的情况下。为了解决这些困难,本研究提出了一种新型的基于物理学的预测校正算法。在提出的计算算法中,使用线性化(MNIM)-N-2方案来预测解决方案,而使用MNIM方案来改善预测性猜测。这种混合数值算法的新颖性在于它结合了(MNIM)-N-2更快收敛的优点和MNIM方案的准确性。该算法还受益于独特的无雅可比牛顿-克雷洛夫(JFNK)方法,该方法有助于摆脱大型雅可比矩阵的形成,从而减少不必要的计算开销。所提出的方法已用于解决由Burgers方程表示的非线性对流扩散问题。给出了一维和二维Burgers方程的计算结果,以证明所开发的新颖算法的有效性以及与现有数值方法相比所提供的优势。 (C)2019 Elsevier Ltd.保留所有权利。

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