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Modeling the glass transition of amorphous networks for shape-memory behavior

机译:为形状记忆行为建模非晶网络的玻璃化转变

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In this paper, a thermomechanical constitutive model was developed for the time-dependent behaviors of the glass transition of amorphous networks. The model used multiple discrete relaxation processes to describe the distribution of relaxation times for stress relaxation, structural relaxation, and stress-activated viscous flow. A non-equilibrium thermodynamic framework based on the fictive temperature was introduced to demonstrate the thermodynamic consistency of the constitutive theory. Experimental and theoretical methods were developed to determine the parameters describing the distribution of stress and structural relaxation times and the dependence of the relaxation times on temperature, structure, and driving stress. The model was applied to study the effects of deformation temperatures and physical aging on the shape-memory behavior of amorphous networks. The model was able to reproduce important features of the partially constrained recovery response observed in experiments. Specifically, the model demonstrated a strain-recovery overshoot for cases programmed below T_g and subjected to a constant mechanical load. This phenomenon was not observed for materials programmed above T_g. Physical aging, in which the material was annealed for an extended period of time below T_g, shifted the activation of strain recovery to higher temperatures and increased significantly the initial recovery rate. For fixed-strain recovery, the model showed a larger overshoot in the stress response for cases programmed below Ts, which was consistent with previous experimental observations. Altogether, this work demonstrates how an understanding of the time-dependent behaviors of the glass transition can be used to tailor the temperature and deformation history of the shape-memory programming process to achieve more complex shape recovery pathways, faster recovery responses, and larger activation stresses. Shape-memory polymers; Structural relaxation; Class transition; Viscoelasticity; Relaxation spectrum
机译:本文针对非晶网络的玻璃化转变随时间变化的行为建立了热力学本构模型。该模型使用多个离散松弛过程来描述应力松弛,结构松弛和应力激活粘性流的松弛时间分布。介绍了一种基于虚拟温度的非平衡热力学框架,以证明本构理论的热力学一致性。开发了实验和理论方法来确定描述应力和结构弛豫时间的分布以及弛豫时间对温度,结构和驱动应力的依赖性的参数。该模型用于研究变形温度和物理老化对非晶网络的形状记忆行为的影响。该模型能够重现实验中观察到的部分受限恢复响应的重要特征。具体而言,对于在T_g以下编程并承受恒定机械负载的情况,该模型显示出应变恢复超调。对于编程为T_g以上的材料,未观察到此现象。物理老化使材料在低于T_g的温度下退火一段较长的时间,从而使应变恢复的激活转移到更高的温度,并显着提高了初始恢复率。对于固定应变恢复,该模型在低于Ts的情况下显示出更大的应力响应过冲,与先前的实验观察结果一致。总而言之,这项工作演示了如何利用对玻璃化转变的随时间变化的行为的了解来定制形状记忆编程过程的温度和变形历史,以实现更复杂的形状恢复路径,更快的恢复响应以及更大的活化度压力。形状记忆聚合物;结构松弛;班级过渡;粘弹性;弛豫谱

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