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A system-level interface sampling and reduction method for component mode synthesis with varying parameters

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  • Cheon, Seunghee
  • Lee, Soobum
  • Lee, Jaehun

Abstract

This paper presents a new interface sampling and reduction method for varying parameters within the framework of the component mode synthesis (CMS) method. In the conventional interpolation-based parametric reduced-order model (IB-PROM) based on CMS, reduced subsystems are synthesized, and interface degrees-of-freedom are reduced via the secondary eigenvalue analysis in the online stage, which is essential to obtain highly reduced system matrices. However, it inhibits rapid parameter updating and requires extra computational resources in the online stage. In the present study, the pre-reduced interface sampling method is proposed by synthesizing substructures and reducing the interface before beginning the online stage. The interface solution is obtained through offline and online adaptation, likewise the procedure of computing the interior solution of previous studies. Additionally, congruence transformations are applied to each reduced interface, which is mandatory for interpolating symmetric positive definite matrices with respect to a new input parameter. As a result, the online performance of IB-PROM is greatly enhanced, showing rapid and near real-time adaptations to the variations in system parameters.

Suggested Citation

  • Cheon, Seunghee & Lee, Soobum & Lee, Jaehun, 2024. "A system-level interface sampling and reduction method for component mode synthesis with varying parameters," Applied Mathematics and Computation, Elsevier, vol. 476(C).
    • Handle: RePEc:eee:apmaco:v:476:y:2024:i:c:s0096300324002431
    DOI: 10.1016/j.amc.2024.128778
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    References listed on IDEAS

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    1. Kim, Jin-Gyun & Seo, Jaho & Lim, Jae Hyuk, 2019. "Novel modal methods for transient analysis with a reduced order model based on enhanced Craig–Bampton formulation," Applied Mathematics and Computation, Elsevier, vol. 344, pages 30-45.
    2. Dietze, Saskia & Grepl, Martin A., 2023. "Reduced order model predictive control for parametrized parabolic partial differential equations," Applied Mathematics and Computation, Elsevier, vol. 453(C).
    3. Uzunca, Murat & Karasözen, Bülent & Aydın, Ayhan, 2023. "Global energy preserving model reduction for multi-symplectic PDEs," Applied Mathematics and Computation, Elsevier, vol. 436(C).
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