基于自适应性粗粒化建模的旋节分解三维膜结构形态设计和力学性能调控

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中文摘要：目前，旋节分解结构因其在设计空间所展现出的巨大潜力得到了广泛的关注，基于旋节分解结构的超材料结构设计焕发新的活力。与受到参数控制显著的三维实体结构相比，膜结构要求在建模过程中采用自适应网格的方法，对三维旋节分解膜结构的力学性能预测仍然存在巨大挑战。本文提出了一种具有定制机械性能的形态设计综合方法，该方法将旋节分解结构与自适应性粗粒化建模相结合，实现具有复合形态特征的整体膜结构建模，并将设计参数与力学性能相关联，确定了伪周期参数β和方向参数组Θ(θ1。θ2，θ3)，以实现各向异性力学性能的优化设计目标。通过参数分析手段，揭示了定制化三维旋节分解膜结构形态参数与实际力学性能间的相关性，提供了结构形态变化和力学性能调整的综合策略，为设计和开发类似三维旋节分解膜结构的定制化功能材料提供可靠的技术手段。

外文标题：Morphological design and tunable mechanical properties of 3D spinodal membrane structures:adaptive coarse-grained modelling

外文摘要：The spinodal decomposition method emerges as a promising methodology,showcasing its potential in exploring the design space for metamaterial structures.However,spinodal structures design is still largely limited to regular structures,due to their relatively easy parameterization and controllability.Efficiently predicting the mechanical properties of 3D spinodal membrane structure remains a challenge,given that the features of the membrane necessitate adaptive mesh through the modelling process.This paper proposes an integrated approach for morphological design with customized mechanical properties,in-corporating the spinodal decomposition method and adaptive coarse-grained modeling,which can produce various morphologies such as lamellar,columnar,and cubic structures.Pseudo-periodic parameter β and orientational parameterΘ(θ1,θ2,θ3)are identified to achieve the optimal goal of anisotropic mechanical properties.Parametric analysis is conducted to reveal the correlation between the customized spinodal structure and mechanical performance.Our work provides an integrated approach for morphological variation and tuning mechanical properties,paving the way for the design and development of customized functional materials similar to 3D spinodal membrane structures.

外文关键词：

Morphological designSpinodal decompositionAdaptive coarse-grained modelingMechanical propertiesParametric design

作者：

相宇杰、田杰、汤可可、王贤锹、仲政

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作者单位：

School of Aerospace Engineering and Applied Mechanics,Tongji University,Shanghai 200092,China

Key Laboratory of AI-aided Airworthiness of Civil Aircraft Structures,Civil Aviation Administration of China,Tongji University Shanghai 200092,China

School of School of Environmental,Civil,Agricultural and Mechanical Engineering,University of Georgia,Athens GA 30602,USA

School of Science,Harbin Institute of Technology,Shenzhen 518055,China

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关键词：

Morphological design Spinodal decomposition Adaptive coarse-grained modeling Mechanical properties Parametric design

基金：

National Natural Science Foundation of ChinaScience and Technology Commission of Shanghai MunicipalityFundamental Research Funds for the Central Universities

项目编号：

1187227821ZR1467200

出版年：

2024

DOI：

10.1007/s10409-024-23655-x

力学学报(英文版)

CSTPCD

影响因子：0.363

ISSN：0567-7718

年,卷(期)：2024.40(8)