We consider a new coarse space for the ASM and RAS preconditioners to solve elliptic partial differential equations on perforated domains, where the numerous polygonal perforations represent structures such as walls and buildings in urban data. With the eventual goal of modelling urban floods by means of the nonlinear Diffusive Wave equation, this contribution focuses on the solution of linear problems on perforated domains. Our coarse space uses a polygonal subdomain partitioning and is spanned by Trefftz-like basis functions that are piecewise linear on the boundary of a subdomain and harmonic inside it. It is based on nodal degrees of freedom that account for the intersection between the perforations and the subdomain boundaries. As a reference, we compare this coarse space to the well-studied Nicolaides coarse space with the same subdomain partitioning. It is known that the Nicolaides space is unable to prevent stagnation in convergence when the subdomains are not connected; we work around this issue by separating each subdomain by disconnected component. Scalability and robustness are tested for multiple data sets based on realistic urban topography. Numerical results show that the new coarse space is very robust and accelerates the number of Krylov iterations when compared to Nicolaides, independent of the complexity of the data.
翻译:本文考虑在扑孔区域上求解椭圆偏微分方程的ASM和RAS预处理器的新型粗模空间,其数值模拟城市洪涝等灾害的发生与扩散。通过使用新型的多边形子域分裂算法,粗模空间采用分段线性的Trefftz样式基函数,在子域边界上是连续的,在其内部是调和的。该粗模空间使用节点自由度来描述扑孔区域与子域边界的交点。我们将其与已有的 Nicolaides 模型进行对比,文中特意解决 Nicolaides 模型在扑孔区域未连接时容易出现收敛停滞的问题。我们在多组包含真实城市地形的数据集上进行了测试,表明新型粗模空间相较于 Nicolaides,具有更高的计算可扩展性和更好的数值解法稳定性,无论数据的复杂性如何,都可以加快 Krylov 迭代的收敛速度。