Based on the basic equations of finite element method,the feature extension layer is embedded into the deep learning model,and a training set generator is developed using Abaqus software interface to achieve single model prediction of the full displacement component of the structure.Using the Keras API under the TensorFlow framework to train a deep learning model for spatial thin shell structures,a quantitative analysis of the prediction performance is conducted.The results show that:the computational efficiency of the deep learning model is significantly improved compared to the simulation model,and the prediction of the maximum displacement and distribution pattern is basically consistent with the simulation results,however there is an increase in error at the 0 displacement boundary.
关键词
深度学习/模型训练/位移场/预测/空间薄壳结构
Key words
deep learning/model training/displacement field/prediction/spatial thin shell structure
维普
万方数据