Stochastic Galerkin method for cloud simulation. Part II: a fully random Navier-Stokes-cloud model
Stochastic Galerkin method for cloud simulation. Part II: a fully random Navier-Stokes-cloud model
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DOI：
10.1016/j.jcp.2023.111987
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发表时间：
2022-04
期刊：
影响因子：
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通讯作者：
Alina Chertock;A. Kurganov;M. Lukácová-Medvidová;P. Spichtinger;B. Wiebe
中科院分区：
文献类型：
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作者：
Alina Chertock;A. Kurganov;M. Lukácová-Medvidová;P. Spichtinger;B. Wiebe
本文是Chertock等人（2019）[8]中提出的工作的延续。研究了弱可压缩流体热云动力学中的不确定性传播。数学模型由多尺度偏微分方程系统控制，其中宏观流体动力学由弱可压缩Navier-Stokes系统描述，微观云动力学由对流-扩散-反应系统模拟。为了量化系统中的不确定性，我们推导并实现了一种广义多项式混沌随机伽辽金方法。与本工作的第一部分不同，我们将考虑限制在部分随机情况下，其中不确定性仅存在于云物理方程中，我们现在研究一个完全随机的navier - stokes -云模型，其中我们也包括宏观流体动力学中的随机性。我们进行了一系列的数值实验，证明了所开发方法的准确性和效率。
This paper is a continuation of the work presented in Chertock et al. (2019) [8]. We study uncertainty propagation in warm cloud dynamics of weakly compressible fluids. The mathematical model is governed by a multiscale system of PDEs in which the macroscopic fluid dynamics is described by a weakly compressible Navier-Stokes system and the microscopic cloud dynamics is modeled by a convection-diffusion-reaction system. In order to quantify uncertainties present in the system, we derive and implement a generalized polynomial chaos stochastic Galerkin method. Unlike the first part of this work, where we restricted our consideration to the partially stochastic case in which the uncertainties were only present in the cloud physics equations, we now study a fully random Navier-Stokes-cloud model in which we include randomness in the macroscopic fluid dynamics as well. We conduct a series of numerical experiments illustrating the accuracy and efficiency of the developed approach.