具有乘法噪声的时变二维/三维随机闭环地热系统的最佳收敛混合有限元方法

IF 1.7 3区 数学 Q2 MATHEMATICS, APPLIED
Xinyue Gao, Yi Qin, Jian Li
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引用次数: 0

摘要

本文开发并研究了一种新的随时间变化的具有乘法噪声的二维/三维随机闭环地热系统。该模型考虑了管道区域的自由流与多孔介质区域的多孔介质流之间的热传递。达西定律和随机纳维-斯托克斯方程分别用于控制管道区和多孔介质区的流动。热方程与流动方程耦合以描述这两个区域的热传递。为了避免次优收敛,提出了一种新的混合有限元方法,该方法利用亥姆霍兹分解驱动乘法噪声。然后,证明了所提方法的稳定性,并得到了全局误差估计的最优收敛阶数(o(\Delta t^{\frac{1}{2}}+h) \)。最后,数值结果表明了所提模型的高效性和数值方法的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimally convergent mixed finite element methods for the time-dependent 2D/3D stochastic closed-loop geothermal system with multiplicative noise

In this paper, a new time-dependent 2D/3D stochastic closed-loop geothermal system with multiplicative noise is developed and studied. This model considers heat transfer between the free flow in the pipe region and the porous media flow in the porous media region. Darcy’s law and stochastic Navier-Stokes equations are used to control the flows in the pipe and porous media regions, respectively. The heat equation is coupled with the flow equation to describe the heat transfer in these both regions. In order to avoid sub-optimal convergence, a new mixed finite element method is proposed by using the Helmholtz decomposition that drives the multiplicative noise. Then, the stability of the proposed method is proved, and we obtain the optimal convergence order \(o(\Delta t^{\frac{1}{2}}+h)\) of global error estimation. Finally, numerical results indicate the efficiency of the proposed model and the accuracy of the numerical method.

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来源期刊
CiteScore
3.00
自引率
5.90%
发文量
68
审稿时长
3 months
期刊介绍: Advances in Computational Mathematics publishes high quality, accessible and original articles at the forefront of computational and applied mathematics, with a clear potential for impact across the sciences. The journal emphasizes three core areas: approximation theory and computational geometry; numerical analysis, modelling and simulation; imaging, signal processing and data analysis. This journal welcomes papers that are accessible to a broad audience in the mathematical sciences and that show either an advance in computational methodology or a novel scientific application area, or both. Methods papers should rely on rigorous analysis and/or convincing numerical studies.
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