发表机构
University of Michigan-Dearborn（密歇根大学迪尔伯恩分校）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出一种面向多输入二次双线性描述符系统的无矩阵矩匹配降阶方法，通过为不同输入通道构造独立投影空间，无需组装全阶矩阵即可高效计算降阶模型，并在二维流动问题中验证了其准确复现瞬态响应的能力。
AI 中文摘要
本文针对多输入二次双线性描述符系统，提出了一种新的矩匹配降阶方法。所提出的方法能够处理同时作用于微分方程和代数方程的多个输入，并为不同的输入通道和输入组合构造独立的投影空间。该方法采用无矩阵算法，无需显式组装或存储全阶系统矩阵和张量，即可计算降阶矩阵和张量。这一特性使该方法特别适用于大规模计算流体动力学问题。针对二维流动问题进行的数值实验表明，所得到的降阶模型能够在多个时变输入下准确复现全阶模型的瞬态响应。
英文摘要
This paper develops a new moment-matching order reduction method for multi-input quadratic-bilinear descriptor systems. The proposed approach accommodates multiple inputs acting on both the differential and algebraic equations and constructs separate projection spaces associated with different input channels and input combinations. The method uses a matrix-free algorithm, allowing the reduced-order matrices and tensors to be computed without explicitly assembling or storing the full-order system matrices and tensors. This feature makes the proposed method particularly suitable for large-scale computational fluid dynamics problems. Numerical experiments carried out for two-dimensional flow problems demonstrate that the resulting reduced-order models accurately reproduce the transient responses of the full-order models under multiple time-varying inputs.
