Progressive damage and failure analysis of CNT-reinforced laminated nanocomposite structures: A multiscale modeling framework

IF 5.7 2区 工程技术 Q1 ENGINEERING, MECHANICAL Engineering Failure Analysis Pub Date : 2025-02-22 DOI:10.1016/j.engfailanal.2025.109452
Panagiotis A. Antoniou , Konstantinos P. Stamoulis , Stelios K. Georgantzinos
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Abstract

This article presents a Multiscale Modeling Framework for the prediction of the progressive damage and failure analysis of laminated composites structures reinforced with carbon nanotubes (CNTs). First, the modified Halpin-Tsai (H-T) model is employed to estimate the mechanical properties of CNT-reinforced matrix. The H-T equation is capable of distinguishing the difference between micro and nanoscale and accounting for factors such as CNT dispersion and curvature. To capture the CNT and surrounding polymer interactions at the microscale, the Young’s modulus of the isolated CNT is evaluated using the equivalent fiber technique. In addition, the Chamis equations are used to predict the stiffness of the nanocomposite lamina. Then, a set of six equations is developed to estimate the ultimate strength of the nanocomposite lamina based on the individual properties of its constituents, including fibers and the CNT-reinforced polymer matrix. Finally, the damage initiation criterion for Fiber-Reinforced Polymer Composites, based on Hashin’s theory and combined with the fracture energy approach is employed to predict the progressive damage and failure behavior of laminated nanocomposite structures, subjected to tensile loads. This analysis considers the effects of CNT critical factors and size. The predictions of the present Multiscale Modeling Framework are in very good agreement with experimental stress–strain data. It has been demonstrated that while the CNT inclusions can enhance the overall strength of nanocomposite laminae, the tensile strength of the nanocomposite beams is markedly influenced by the microstructural characteristics of CNTs, which significantly reduce the CNTs effectiveness in reinforcing Fiber-Reinforced Polymer Composites.
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碳纳米管增强层状纳米复合材料结构的渐进损伤和失效分析:一个多尺度建模框架
本文提出了一种多尺度模型框架,用于预测碳纳米管增强层合复合材料结构的渐进损伤和失效分析。首先,采用改进的Halpin-Tsai (H-T)模型对碳纳米管增强基体的力学性能进行估计。H-T方程能够区分微观和纳米尺度的差异,并考虑碳纳米管色散和曲率等因素。为了在微观尺度上捕捉碳纳米管和周围聚合物的相互作用,使用等效纤维技术评估了隔离碳纳米管的杨氏模量。此外,利用Chamis方程预测了纳米复合材料层的刚度。然后,基于其组分(包括纤维和碳纳米管增强聚合物基体)的单个特性,开发了一组六个方程来估计纳米复合材料层的极限强度。最后,基于Hashin理论,结合断裂能方法,建立了纤维增强聚合物复合材料的损伤起裂准则,预测了层状纳米复合材料结构在拉伸载荷作用下的渐进损伤和破坏行为。该分析考虑了碳纳米管的关键因素和尺寸的影响。多尺度模拟框架的预测结果与实验应力应变数据吻合较好。研究表明,虽然碳纳米管包裹体可以提高纳米复合材料层的整体强度,但纳米复合材料梁的抗拉强度受到CNTs的微观结构特性的显著影响,这显著降低了CNTs在增强纤维增强聚合物复合材料中的有效性。
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来源期刊
Engineering Failure Analysis
Engineering Failure Analysis 工程技术-材料科学:表征与测试
CiteScore
7.70
自引率
20.00%
发文量
956
审稿时长
47 days
期刊介绍: Engineering Failure Analysis publishes research papers describing the analysis of engineering failures and related studies. Papers relating to the structure, properties and behaviour of engineering materials are encouraged, particularly those which also involve the detailed application of materials parameters to problems in engineering structures, components and design. In addition to the area of materials engineering, the interacting fields of mechanical, manufacturing, aeronautical, civil, chemical, corrosion and design engineering are considered relevant. Activity should be directed at analysing engineering failures and carrying out research to help reduce the incidences of failures and to extend the operating horizons of engineering materials. Emphasis is placed on the mechanical properties of materials and their behaviour when influenced by structure, process and environment. Metallic, polymeric, ceramic and natural materials are all included and the application of these materials to real engineering situations should be emphasised. The use of a case-study based approach is also encouraged. Engineering Failure Analysis provides essential reference material and critical feedback into the design process thereby contributing to the prevention of engineering failures in the future. All submissions will be subject to peer review from leading experts in the field.
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