Prediction of the elastic properties and strength of unidirectional carbon fiber reinforced polymers based on representative volume element simulation

IF 6.5 2区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY
Miao Su , Lei Liu , Yuxi Xie , Hui Peng , Chongjie Kang
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引用次数: 0

Abstract

The mechanical properties of unidirectional carbon fiber reinforced polymer (UD-CFRP), such as its elastic modulus and ultimate strength, are crucial and fundamental indicators. Examining these properties from a microscopic perspective through numerical simulations can provide valuable insights for material modification and the design of new materials. This study employs a micromechanics-based representative volume element (RVE) method to predict the macroscopic mechanical properties of UD-CFRP. The results demonstrate that the established RVE models accurately predict the elastic and shear modulus, as well as the ultimate tensile and compressive strength of UD-CFRP. Additionally, simulations of 300 RVE models with varying input parameter combinations were performed, generating a dataset that encompasses both microstructure parameters and macroscopic mechanical properties of UD-CFRP. Using the dataset, random forest regression models were created and SHAP analysis was performed to identify the key microstructural parameters with significant feature importance. Subsequently, we systematically investigated their effects on the macroscopic mechanical properties of UD-CFRP. In the end, simplified analytical prediction formulas were proposed to evaluate the macroscopic mechanical properties of UD-CFRP, demonstrating superior predictive performance compared to existing formulas.
基于代表性体积元模拟的单向碳纤维增强聚合物弹性性能及强度预测
单向碳纤维增强聚合物(UD-CFRP)的力学性能,如弹性模量和极限强度,是至关重要的基本指标。通过数值模拟从微观角度研究这些特性可以为材料改性和新材料的设计提供有价值的见解。本研究采用基于细观力学的代表性体积元(RVE)方法预测UD-CFRP的宏观力学性能。结果表明,所建立的RVE模型能够准确预测UD-CFRP的弹性模量、剪切模量以及极限抗拉强度和抗压强度。此外,对300个不同输入参数组合的RVE模型进行了模拟,生成了包含UD-CFRP微观结构参数和宏观力学性能的数据集。利用该数据集建立随机森林回归模型,并进行SHAP分析,以识别具有显著特征重要性的关键微观结构参数。随后,我们系统地研究了它们对UD-CFRP宏观力学性能的影响。最后,提出了用于评价UD-CFRP宏观力学性能的简化分析预测公式,与现有公式相比,预测性能优越。
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来源期刊
CiteScore
7.60
自引率
19.40%
发文量
842
审稿时长
63 days
期刊介绍: Case Studies in Construction Materials provides a forum for the rapid publication of short, structured Case Studies on construction materials. In addition, the journal also publishes related Short Communications, Full length research article and Comprehensive review papers (by invitation). The journal will provide an essential compendium of case studies for practicing engineers, designers, researchers and other practitioners who are interested in all aspects construction materials. The journal will publish new and novel case studies, but will also provide a forum for the publication of high quality descriptions of classic construction material problems and solutions.
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