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  • Open Access

    ARTICLE

    Explicit Topology Optimization Design of Stiffened Plate Structures Based on the Moving Morphable Component (MMC) Method

    Xudong Jiang1, Chang Liu1,2,*, Shaohui Zhang3, Weisheng Zhang1,2, Zongliang Du1,2, Xiaoyu Zhang3, Huizhong Zeng3, Xu Guo1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 809-838, 2023, DOI:10.32604/cmes.2023.023561

    Abstract This paper proposes an explicit method for topology optimization of stiffened plate structures. The present work is devoted to simultaneously optimizing stiffeners’ shape, size and layout by seeking the optimal geometry parameters of a series of moving morphable components (MMC). The stiffeners with straight skeletons and the stiffeners with curved skeletons are considered to enhance the modeling and optimization capability of the current approach. All the stiffeners are represented under the Lagrangian-description framework in a fully explicit way, and the adaptive ground structure method, as well as dynamically updated plate/shell elements, is used to obtain optimized designs with more accurate… More > Graphic Abstract

    Explicit Topology Optimization Design of Stiffened Plate Structures Based on the Moving Morphable Component (MMC) Method

  • Open Access

    ARTICLE

    Inverse Load Identification in Stiffened Plate Structure Based on in situ Strain Measurement

    Yihua Wang1, Zhenhuan Zhou1, Hao Xu1,*, Shuai Li2, Zhanjun Wu1

    Structural Durability & Health Monitoring, Vol.15, No.2, pp. 85-101, 2021, DOI:10.32604/sdhm.2021.014256

    Abstract For practical engineering structures, it is usually difficult to measure external load distribution in a direct manner, which makes inverse load identification important. Specifically, load identification is a typical inverse problem, for which the models (e.g., response matrix) are often ill-posed, resulting in degraded accuracy and impaired noise immunity of load identification. This study aims at identifying external loads in a stiffened plate structure, through comparing the effectiveness of different methods for parameter selection in regulation problems, including the Generalized Cross Validation (GCV) method, the Ordinary Cross Validation method and the truncated singular value decomposition method. With demonstrated high accuracy,… More >

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