论文标题

非线性模型订单降低使用时空域的差异变换

Nonlinear Model Order Reduction using Diffeomorphic Transformations of a Space-Time Domain

论文作者

Kleikamp, Hendrik, Ohlberger, Mario, Rave, Stephan

论文摘要

在许多应用中,例如,在描述流体或气体动力学时,双曲线保护定律自然出现在保守量的系统(例如质量或能量)的建模中。这些类型的方程式表现出高度非线性的行为,例如冲击形成或冲击相互作用。在参数化双曲方程的情况下,考虑到不同的传输速度,这些非线性和强大的运输效应会导致高度非线性的溶液歧管。该解决方案歧管不能通过线性子空间正确近似。为此,需要采用非线性减少双曲线保护定律的方法。我们提出了一种新的非线性模型订购降低方法,该方法特别适合具有不连续溶液的双曲线方程。该方法基于时空离散化,并采用了基础时空域的差异转换来对齐不连续性。为了得出差异性的还原模型,使用指数映射将差异组的谎言组结构与相应的速度场相关联。在速度场的线性空间中,可以应用标准模型订购降低技术(例如正交分解),以提取还原的子空间。对于带有两个合并冲击的参数化汉堡方程,数值实验显示了该方法的潜力。

In many applications, for instance when describing dynamics of fluids or gases, hyperbolic conservation laws arise naturally in the modeling of conserved quantities of a system, like mass or energy. These types of equations exhibit highly nonlinear behaviors like shock formation or shock interaction. In the case of parametrized hyperbolic equations, where, for instance, varying transport velocities are considered, these nonlinearities and strong transport effects result in a highly nonlinear solution manifold. This solution manifold cannot be approximated properly by linear subspaces. To this end, nonlinear approaches for model order reduction of hyperbolic conservation laws are required. We propose a new method for nonlinear model order reduction that is especially well-suited for hyperbolic equations with discontinuous solutions. The approach is based on a space-time discretization and employs diffeomorphic transformations of the underlying space-time domain to align the discontinuities. To derive a reduced model for the diffeomorphisms, the Lie group structure of the diffeomorphism group is used to associate diffeomorphisms with corresponding velocity fields via the exponential map. In the linear space of velocity fields, standard model order reduction techniques, such as proper orthogonal decomposition, can be applied to extract a reduced subspace. For a parametrized Burgers' equation with two merging shocks, numerical experiments show the potential of the approach.

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