We consider the time-dependent Stokes-Darcy problem as a model case for the challenges involved in solving coupled systems. Keeping the model, its discretization, and the underlying numerics for the subproblems in the free-flow domain and the porous medium constant, we focus on different solver approaches for the coupled problem. We compare a partitioned coupling approach using the coupling library preCICE with a monolithic block-preconditioned one that is tailored to different formulations of the problem. Both approaches enable the reuse of already available iterative solvers and preconditioners, in our case, from the DuMux framework. Our results indicate that the approaches can yield performance and scalability improvements compared to using direct solvers: Partitioned coupling is able to solve large problems faster if iterative solvers with suitable preconditioners are applied for the subproblems. The monolithic approach shows even stronger requirements on preconditioning, as standard simple solvers fail to converge. Our monolithic block preconditioning yields the fastest runtimes for large systems, but they vary strongly with the preconditioner configuration. Interestingly, using a specialized Uzawa preconditioner for the Stokes subsystem leads to overall increased runtimes compared to block preconditioners utilizing a more general algebraic multigrid. This highlights that optimizing for the non-coupled cases does not always pay off.
翻译:我们把依赖时间的斯托克斯-达西问题视为解决连接系统所涉挑战的典型案例。 保持模型、 其离散性, 以及对于自由流域和多孔介质常数中子问题的基本数字, 我们集中关注不同的解决问题方法。 我们比较了使用混合图书馆预科和单一整块预设方法的分割式混合方法, 以适合问题不同公式的单一整块预设方法。 两种办法都使得已经具备的迭代解答器和先决条件者能够从 Dumux 框架中重新利用。 我们的结果表明, 与直接解答器相比, 这些方法可以产生性能和可变性改进: 如果对子问题采用具有适当先决条件的迭代解答器, 分解式混合方法能够更快地解决大问题。 单一整块方法显示, 对先决条件的要求甚至更强烈, 因为标准的简单解答器无法趋同。 我们的单一整块预设后, 使大型系统能产生最迅速的运行时间, 但是它们与前置系统配置相比, 差异很大。 分解式的平流性组合将比普通的固定前置前置前置前置方案, 将比整个平级更需要增加一个普通的Staricregregrela 。