{"title":"Virtual beam-based prior interface reduction for optimizing plate substructures with complex interface geometry","authors":"Tuan Anh Bui, Jun-Sik Kim, Junyoung Park","doi":"10.1007/s00419-025-02881-w","DOIUrl":null,"url":null,"abstract":"<div><p>Collaboration among multiple companies on a project to design and produce complex structures offers numerous benefits, including reduced time and production costs, as well as enhanced product quality. Component mode synthesis techniques can be used to divide the entire structure into many substructures, thus distributing the design tasks among various groups. When substructures have a large number of physical degrees of freedom at the interface, interface reduction is necessary to ensure a reasonable computation time. Prior interface reduction methods, such as the orthogonal polynomial method, allow reduced-order models of substructures to be constructed independently. This independence allows the work of different teams to be non-overlapping, thereby increasing overall labor productivity. However, the orthogonal polynomial method encounters limitations when applied to interfaces with complex geometries. To address these challenges, this paper proposes a new prior interface reduction method. The interface reduction basis will be created from the eigenvalue analysis of a virtual beam, which mirrors the interface geometry. The examples presented in this paper show that the proposed method achieved high accuracy while maintaining a compact reduction basis.</p></div>","PeriodicalId":477,"journal":{"name":"Archive of Applied Mechanics","volume":"95 7","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Archive of Applied Mechanics","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.1007/s00419-025-02881-w","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MECHANICS","Score":null,"Total":0}
引用次数: 0
Abstract
Collaboration among multiple companies on a project to design and produce complex structures offers numerous benefits, including reduced time and production costs, as well as enhanced product quality. Component mode synthesis techniques can be used to divide the entire structure into many substructures, thus distributing the design tasks among various groups. When substructures have a large number of physical degrees of freedom at the interface, interface reduction is necessary to ensure a reasonable computation time. Prior interface reduction methods, such as the orthogonal polynomial method, allow reduced-order models of substructures to be constructed independently. This independence allows the work of different teams to be non-overlapping, thereby increasing overall labor productivity. However, the orthogonal polynomial method encounters limitations when applied to interfaces with complex geometries. To address these challenges, this paper proposes a new prior interface reduction method. The interface reduction basis will be created from the eigenvalue analysis of a virtual beam, which mirrors the interface geometry. The examples presented in this paper show that the proposed method achieved high accuracy while maintaining a compact reduction basis.
期刊介绍:
Archive of Applied Mechanics serves as a platform to communicate original research of scholarly value in all branches of theoretical and applied mechanics, i.e., in solid and fluid mechanics, dynamics and vibrations. It focuses on continuum mechanics in general, structural mechanics, biomechanics, micro- and nano-mechanics as well as hydrodynamics. In particular, the following topics are emphasised: thermodynamics of materials, material modeling, multi-physics, mechanical properties of materials, homogenisation, phase transitions, fracture and damage mechanics, vibration, wave propagation experimental mechanics as well as machine learning techniques in the context of applied mechanics.