TY  - EJOU
AU  - Cheng, Yu 
AU  - Huang, Yajun 
AU  - Li, Shuai 
AU  - Zhou, Zhongbin 
AU  - Yuan, Xiaohui 
AU  - Xu, Yanming 

TI  - A Deep Learning Approach to Shape Optimization Problems for Flexoelectric Materials Using the Isogeometric Finite Element Method
T2  - Computer Modeling in Engineering \& Sciences

PY  - 2024
VL  - 139
IS  - 2
SN  - 1526-1506

AB  - A new approach for flexoelectric material shape optimization is proposed in this study. In this work, a proxy model based on artificial neural network (ANN) is used to solve the parameter optimization and shape optimization problems. To improve the fitting ability of the neural network, we use the idea of pre-training to determine the structure of the neural network and combine different optimizers for training. The isogeometric analysis-finite element method (IGA-FEM) is used to discretize the flexural theoretical formulas and obtain samples, which helps ANN to build a proxy model from the model shape to the target value. The effectiveness of the proposed method is verified through two numerical examples of parameter optimization and one numerical example of shape optimization.
KW  - Shape optimization; deep learning; flexoelectric structure; finite element method; isogeometric

DO  - 10.32604/cmes.2023.045668