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arXiv 1802.06263math.NAcs.NA

随机多尺度通量基对于斯托克斯-达西流

Stochastic multiscale flux basis for Stokes-Darcy flows

University of Pittsburgh(匹兹堡大学)

Ilona Ambartsumyan, Eldar Khattatov, ChangQing Wang, Ivan Yotov

AI总结:

本文提出三种算法用于耦合斯托克斯和达西流的不确定性量化,通过随机(collocation)网格和多尺度混合有限元方法结合多尺度通量基,减少计算成本。

摘要:

三种算法被开发用于耦合斯托克斯和达西流模型的不确定性量化。多孔介质可能由多个具有不同性质的区域组成。渗透率被建模为非平稳随机变量,其对数表示为局部卡拉什-洛埃夫(KL)展开的和。该问题通过随机(collocation)在张量积或稀疏网格上近似,结合多尺度混合有限元方法进行空间离散化。非重叠域分解算法将全局问题转化为粗尺度的 mortar 接口问题,通过迭代求解器在每个随机实现中求解。在传统实现中,每个子域在每次接口迭代中求解局部狄利克雷或Neumann问题。为了减少这种成本,引入了两种额外的算法,基于确定性或随机多尺度通量基。基由每个mortar自由度的局部通量(或速度迹)响应组成。它由每个子域在接口迭代开始前独立计算。使用多尺度通量基避免了每次迭代都需要子域求解的需要。确定性基在每个随机(collocation)处计算,仅用于该实现。随机基是在所有局部实现的KL区域的进一步循环中形成的,在随机(collocation)开始前计算。它在多个实现中被重用。数值测试展示了三种算法的性能,随机多尺度通量基在计算成本上显示出显著节省。

英文摘要:

Three algorithms are developed for uncertainty quantification in modeling coupled Stokes and Darcy flows. The porous media may consist of multiple regions with different properties. The permeability is modeled as a non-stationary stochastic variable, with its log represented as a sum of local Karhunen-Loève (KL) expansions. The problem is approximated by stochastic collocation on either tensor-product or sparse grids, coupled with a multiscale mortar mixed finite element method for the spatial discretization. A non-overlapping domain decomposition algorithm reduces the global problem to a coarse scale mortar interface problem, which is solved by an iterative solver, for each stochastic realization. In the traditional implementation, each subdomain solves a local Dirichlet or Neumann problem in every interface iteration. To reduce this cost, two additional algorithms based on deterministic or stochastic multiscale flux basis are introduced. The basis consists of the local flux (or velocity trace) responses from each mortar degree of freedom. It is computed by each subdomain independently before the interface iteration begins. The use of the multiscale flux basis avoids the need for subdomain solves on each iteration. The deterministic basis is computed at each stochastic collocation and used only at this realization. The stochastic basis is formed by further looping over all local realizations of a subdomain's KL region before the stochastic collocation begins. It is reused over multiple realizations. Numerical tests are presented to illustrate the performance of the three algorithms, with the stochastic multiscale flux basis showing significant savings in computational cost.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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