Abstract

In this paper, an Artificial Intelligence (AI) model is constructed for the behavior prediction, i.e. Young’s modulus, of polymer/carbon-nanotube (CNTs) composites. The AI is proposed to overcome the difficulties when studying the properties of novel composite materials, for example the time-consuming of experimental studies of resource-consuming of other numerical methods. Artificial Neural Network (ANN) model was chosen and optimized in architecture based on a parametric study. The main objective of this study is to firstly confirm that the proposed AI method performs well for nanocomposites and it can then be optimized in terms of computational time and resources in further studies. The obtained results have shown that the proposed model exhibits great performance in both training and testing phases, where the correlation coefficient is 0.986 for training part and 0.978 for the testing part.

摘要

在本文中，为聚合物/碳纳米管(CNT) 复合材料的行为预测，即杨氏模量，构建了人工智能(AI) 模型。提出人工智能是为了克服研究新型复合材料性能时的困难，例如其他数值方法的资源消耗实验研究的耗时。人工神经网络 (ANN) 模型是在基于参数研究的架构中选择和优化的。本研究的主要目的是首先确认所提出的 AI 方法对纳米复合材料表现良好，然后可以在进一步研究中在计算时间和资源方面进行优化。获得的结果表明，所提出的模型在训练和测试阶段都表现出良好的性能，相关系数为 0。