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用于双稳态聚合物复合材料结构的统一高阶半解析模型与数值模拟

A Unified High-Order Semianalytical Model and Numerical Simulation for Bistable Polymer Composite Structures.

作者信息

Sun Min, Gao Weiliang, Zhang Zheng, Shen Hongcheng, Zhou Yisong, Wu Huaping, Jiang Shaofei

机构信息

College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310014, China.

Key Laboratory of Special Purpose Equipment and Advanced Processing Technology, Ministry of Education and Zhejiang Province, Zhejiang University of Technology, Hangzhou 310014, China.

出版信息

Polymers (Basel). 2022 Feb 20;14(4):818. doi: 10.3390/polym14040818.

Abstract

Bistable polymer composite structures are morphing shells that can change shape and maintain two stable configurations. At present, mainly two types of bistable polymer composite structures are being studied: cross-ply laminates and antisymmetric cylindrical shells. This paper proposes a unified semianalytical model based on the extensible deformation assumption and nonlinear theory of plates and shells to predict bistability. Moreover, the higher-order theoretical model is extended for better prediction accuracy, while the number of degrees of freedom is not increased; this ensures a lower computational cost. Finally, based on these theoretical models, the main factors affecting the stable characteristic of the two bistable polymer composite structures are determined by comparing the models of various orders. The main challenges in describing the bistable behavior, such as bifurcation points and the curvatures of stable states, are addressed through prediction of the corner transversal displacement in stable configurations. The results obtained from the theoretical model are validated through nonlinear finite element analysis.

摘要

双稳态聚合物复合材料结构是能够改变形状并保持两种稳定构型的变形壳体。目前,主要研究的双稳态聚合物复合材料结构有两种类型:正交铺层板和反对称圆柱壳。本文基于可扩展变形假设以及板壳非线性理论,提出了一个统一的半解析模型来预测双稳态。此外,在不增加自由度数量的情况下,扩展了高阶理论模型以提高预测精度,这确保了较低的计算成本。最后,基于这些理论模型,通过比较不同阶次的模型,确定了影响两种双稳态聚合物复合材料结构稳定特性的主要因素。通过预测稳定构型中的角向横向位移,解决了描述双稳态行为时的主要挑战,如分岔点和稳定状态的曲率等问题。通过非线性有限元分析对理论模型得到的结果进行了验证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c67d/8963123/4f0fb831b18a/polymers-14-00818-g001.jpg

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