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arXiv 2512.04592math.NAcs.NAphysics.comp-phphysics.flu-dyn
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用于不可压缩流体的降阶模型的稳定自适应时间步长方法

Stable self-adaptive timestepping for Reduced Order Models for incompressible flows

Technical University of Catalonia(加泰罗尼亚理工大学);Centrum Wiskunde & Informatica(荷兰数学与计算机科学中心);Eindhoven University of Technology(埃因霍温理工大学)

Josep Plana-Riu, Henrik Rosenberger, Benjamin Sanderse, F. Xavier Trias

AI总结:

本文提出RedEigCD方法,通过线性稳定性理论为降阶模型提供自适应时间步长,证明降阶模型的时间步长不小于全阶模型,实验显示其时间步长可提升40倍而不影响精度。

摘要:

本文介绍RedEigCD,一种专为不可压缩纳维-斯托克斯方程降阶模型(ROMs)设计的自适应时间步长技术。基于线性稳定性概念,该方法通过直接利用与降阶算子相关的矩阵的精确谱信息,对所用时间积分方案的稳定性函数进行约束。与传统基于误差的自适应方法不同,RedEigCD依赖于对流传导ROM算子的特征值界,其计算在降阶尺度上可行且完全保持ROM的在线效率。本文的核心理论贡献是基于Bendixson和Rao的结合定理,证明在线性化假设下,投影降阶模型的最大稳定时间步长不小于其对应全阶模型(FOMs)的。数值实验显示,对于周期性和非均匀边界条件,RedEigCD的时间步长可提升至全阶模型的40倍,而不影响精度。该方法建立了线性稳定性理论与降阶建模之间的新联系,为高效、自调节的降阶模型积分提供了系统路径。

英文摘要:

This work introduces RedEigCD, the first self-adaptive timestepping technique specifically tailored for reduced-order models (ROMs) of the incompressible Navier-Stokes equations. Building upon linear stability concepts, the method adapts the timestep by directly bounding the stability function of the employed time integration scheme using exact spectral information of matrices related to the reduced operators. Unlike traditional error-based adaptive methods, RedEigCD relies on the eigenbounds of the convective and diffusive ROM operators, whose computation is feasible at reduced scale and fully preserves the online efficiency of the ROM. A central theoretical contribution of this work is the proof, based on the combined theorems of Bendixson and Rao, that, under linearized assumptions, the maximum stable timestep for projection-based ROMs is shown to be larger than or equal to that of their corresponding full-order models (FOMs). Numerical experiments for both periodic and non-homogeneous boundary conditions demonstrate that RedEigCD yields stable timestep increases up to a factor 40 compared to the FOM, without compromising accuracy. The methodology thus establishes a new link between linear stability theory and reduced-order modeling, offering a systematic path towards efficient, self-regulating ROM integration in incompressible flow simulations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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