Predicting the Mechanical Behavior of a Bioinspired Nanocomposite through Machine Learning  

作　　者：Xingzi Yang Wei Gao Xiaodu Wang Xiaowei Zeng 

机构地区：[1]Department of Mechanical Engineering,University of Texas at San Antonio,San Antonio,TX,78249,USA [2]Department of Mechanical Engineering,Texas A&M University,College Station,TX,77843,USA

出　　处：《Computer Modeling in Engineering & Sciences》2024年第8期1299-1313,共15页工程与科学中的计算机建模（英文）

摘　　要：The bioinspired nacre or bone structure represents a remarkable example of tough,strong,lightweight,and multifunctional structures in biological materials that can be an inspiration to design bioinspired high-performance materials.The bioinspired structure consists of hard grains and soft material interfaces.While the material interface has a very low volume percentage,its property has the ability to determine the bulk material response.Machine learning technology nowadays is widely used in material science.A machine learning model was utilized to predict the material response based on the material interface properties in a bioinspired nanocomposite.This model was trained on a comprehensive dataset of material response and interface properties,allowing it to make accurate predictions.The results of this study demonstrate the efficiency and high accuracy of the machine learning model.The successful application of machine learning into the material property prediction process has the potential to greatly enhance both the efficiency and accuracy of the material design process.

关 键 词：Bioinspired nanocomposite computational model machine learning finite element material interface 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程] TB33[自动化与计算机技术—控制科学与工程]