论文标题
动态模式分解作为时间相关的部分微分方程的分析工具
Dynamic mode decomposition as an analysis tool for time-dependent partial differential equations
论文作者
论文摘要
通过在两个且更大的维度中求解部分微分方程来获得的时间依赖性领域迅速淹没了人脑的分析能力。可以通过使用标量减少来获得对时间行为的有意义的洞察力，但是，这会带来空间细节的损失。动态模式分解是一种数据驱动的分析方法，该方法通过识别振荡空间结构及其相应频率来解决此问题。本文介绍了该算法，并通过将分解方法应用于一系列日益复杂的示例中提供了对结果的物理解释。
The time-dependent fields obtained by solving partial differential equations in two and more dimensions quickly overwhelm the analytical capabilities of the human brain. A meaningful insight into the temporal behaviour can be obtained by using scalar reductions, which, however, come with a loss of spatial detail. Dynamic Mode Decomposition is a data-driven analysis method that solves this problem by identifying oscillating spatial structures and their corresponding frequencies. This paper presents the algorithm and provides a physical interpretation of the results by applying the decomposition method to a series of increasingly complex examples.
