论文标题

完全耦合的非线性化学力学问题中的整体平行重叠施瓦兹方法

Monolithic parallel overlapping Schwarz methods in fully-coupled nonlinear chemo-mechanics problems

论文作者

Kiefer, Bjoern, Prüger, Stefan, Rheinbach, Oliver, Röver, Friederike

论文摘要

我们将水凝胶的肿胀视为化学机械问题的一个例子,与机械平衡关系和质量扩散之间的强耦合。该问题使用时间阐释方法将耗散电位依赖于变形和溶胀体积分数以获得对称矩阵,通常更适合迭代求解器。 MPI平行实现使用软件库Deal.ii,p4est和Frosch(稳健重叠的Schwarz快速)。 Frosch是Trilinos库的一部分,以完全代数模式使用,即,从整体系统矩阵构造了预处理,而无需明确使用问题结构。考虑到标准的GDSW(广义Dryja-Smith-Widlund)粗糙空间和较新的粗大空间,使用多达512个核心研究了强大和弱的并行可伸缩性。 FROSCH求解器适用于此处考虑的处理器核心范围内的耦合问题,尽管对于完全代数模式无法预期(并且无法观察到)数值可缩放性。在我们的强大可伸缩性研究中,与线性弹性问题相比,每次牛顿迭代的平均krylov迭代次数高达6倍。但是,在预处理中轻度使用问题结构,可以将该数字降低到两个倍,并且重要的是,还可以通过实验实现数值可伸缩性。然而,由于实现了更快的解决方案时间,因此完全代数模式仍然是可取的。

We consider the swelling of hydrogels as an example of a chemo-mechanical problem with strong coupling between the mechanical balance relations and the mass diffusion. The problem is cast into a minimization formulation using a time-explicit approach for the dependency of the dissipation potential on the deformation and the swelling volume fraction to obtain symmetric matrices, which are typically better suited for iterative solvers. The MPI-parallel implementation uses the software libraries deal.II, p4est and FROSch (Fast of Robust Overlapping Schwarz). FROSch is part of the Trilinos library and is used in fully algebraic mode, i.e., the preconditioner is constructed from the monolithic system matrix without making explicit use of the problem structure. Strong and weak parallel scalability is studied using up to 512 cores, considering the standard GDSW (Generalized Dryja-Smith-Widlund) coarse space and the newer coarse space with reduced dimension. The FROSch solver is applicable to the coupled problems within in the range of processor cores considered here, although numerical scalablity cannot be expected (and is not observed) for the fully algebraic mode. In our strong scalability study, the average number of Krylov iterations per Newton iteration is higher by a factor of up to six compared to a linear elasticity problem. However, making mild use of the problem structure in the preconditioner, this number can be reduced to a factor of two and, importantly, also numerical scalability can then be achieved experimentally. Nevertheless, the fully algebraic mode is still preferable since a faster time to solution is achieved.

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