A semi-localized reduced interface sampling scheme for dynamic substructuring method-based parametric reduced-order modelling

Seunghee Cheon, Jaehun Lee

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper proposes the semi-localized interface sampling based on conventional interpolation based parametric component mode synthesis (IB-PCMS). The conventional IB-PCMS addressed amount of computational resources required for the offline stage with sbstructural-level sampling, without considering full-system. Therefore, this approach enables more flexible reflection of design updates. On the other hand, the interface degrees-of freedom are fully retained without reduction in the CMS method for subcomponents synthesis. For this reason, the secondary eigenvalue analysis should be computed for interface reduction to achieve a highly-reduced system. In the previous IB-PCMS, substructures are synthesized and interface is reduced in the online stage. This additional computation hinders rapid responses with respect to parameter updating. To address this issue, the reduced interface sampling scheme is proposed by priory computing characteristic constraint (CC) modes. In addition, a semi-localized interface reduction method is newly proposed to efficiently construct reduced interface samples considering the parameter-dependent system. As a result, near real-time operation for the multi-query system can be achieved.

Original languageEnglish
Title of host publicationAIAA SciTech Forum and Exposition, 2024
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624107115
DOIs
StatePublished - 2024
EventAIAA SciTech Forum and Exposition, 2024 - Orlando, United States
Duration: 8 Jan 202412 Jan 2024

Publication series

NameAIAA SciTech Forum and Exposition, 2024

Conference

ConferenceAIAA SciTech Forum and Exposition, 2024
Country/TerritoryUnited States
CityOrlando
Period8/01/2412/01/24

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