Automating embedded analysis capabilities and managing software complexity in multiphysics simulation, Part II: Application to partial differential equations
Automating embedded analysis capabilities and managing software complexity in multiphysics simulation, Part II: Application to partial differential equations
复制标题
自动化嵌入式分析功能并管理多物理场仿真中的软件复杂性，第二部分：在偏微分方程中的应用
作者：
R. Pawlowski;E. Phipps;A. Salinger;S. Owen;C. Siefert;M. Staten
基于模板的泛型编程方法在本系列论文的第一部分[Sci.程序. 20 2012，197- 219]，其将编程物理模型的开发工作与计算嵌入式分析算法所需的附加量（诸如导数）的开发工作分开。在本文中，我们描述了使用基于模板的通用编程方法的偏微分方程偏微分方程的模拟和分析的实施细节。我们详细介绍了我们遇到的几个障碍，以及为克服这些障碍而开发的一些软件基础设施。最后，我们展示了一个三维PDE应用程序的形状优化和不确定性量化结果。
A template-based generic programming approach was presented in Part I of this series of papers [Sci. Program. 20 2012, 197--219] that separates the development effort of programming a physical model from that of computing additional quantities, such as derivatives, needed for embedded analysis algorithms. In this paper, we describe the implementation details for using the template-based generic programming approach for simulation and analysis of partial differential equations PDEs. We detail several of the hurdles that we have encountered, and some of the software infrastructure developed to overcome them. We end with a demonstration where we present shape optimization and uncertainty quantification results for a 3D PDE application.