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用于热致编织织物增强形状记忆聚合物复合材料的三维各向异性热机械模型

A 3D Anisotropic Thermomechanical Model for Thermally Induced Woven-Fabric-Reinforced Shape Memory Polymer Composites.

作者信息

Wang Yingyu, Wang Zhiyi, Ma Jia, Luo Chao, Fang Guangqiang, Peng Xiongqi

机构信息

Institute of Aerospace System Engineering Shanghai, Shanghai 201108, China.

Space Structure and Mechanism Technology Laboratory of China Aerospace Science and Technology Group Co., Ltd., Shanghai 201108, China.

出版信息

Sensors (Basel). 2023 Jul 17;23(14):6455. doi: 10.3390/s23146455.

Abstract

Soft robotic grippers offer great advantages over traditional rigid grippers with respect to grabbing objects with irregular or fragile shapes. Shape memory polymer composites are widely used as actuators and holding elements in soft robotic grippers owing to their finite strain, high specific strength, and high driving force. In this paper, a general 3D anisotropic thermomechanical model for woven fabric-reinforced shape memory polymer composites (SMPCs) is proposed based on Helmholtz free energy decomposition and the second law of thermodynamics. Furthermore, the rule of mixtures is modified to describe the stress distribution in the SMPCs, and stress concentration factors are introduced to account for the shearing interaction between the fabric and matrix and warp yarns and weft yarns. The developed model is implemented with a user material subroutine (UMAT) to simulate the shape memory behaivors of SMPCs. The good consistency between the simulation results and experimental validated the proposed model. Furthermore, a numerical investigation of the effects of yarn orientation on the shape memory behavior of the SMPC soft gripper was also performed.

摘要

与传统刚性夹具相比,软机器人夹具在抓取形状不规则或易碎的物体方面具有很大优势。形状记忆聚合物复合材料因其有限应变、高比强度和高驱动力,被广泛用作软机器人夹具中的致动器和夹持元件。本文基于亥姆霍兹自由能分解和热力学第二定律,提出了一种用于机织织物增强形状记忆聚合物复合材料(SMPC)的通用三维各向异性热机械模型。此外,对混合法则进行了修正,以描述SMPC中的应力分布,并引入应力集中系数来考虑织物与基体以及经纱和纬纱之间的剪切相互作用。通过用户材料子程序(UMAT)实现了所开发的模型,以模拟SMPC的形状记忆行为。模拟结果与实验之间的良好一致性验证了所提出的模型。此外,还对纱线取向对SMPC软夹具形状记忆行为的影响进行了数值研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17d6/10383039/a8cba9a2cf21/sensors-23-06455-g001.jpg

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