Xiangru He1, Ying Deng1, Zefu Li1, Jie Zhi1,2, Yonglin Chen1,2, Weidong Yang1,2,3,*, Yan Li1,2,3,*
The International Conference on Computational & Experimental Engineering and Sciences, Vol.34, No.1, pp. 1-1, 2025, DOI:10.32604/icces.2025.012395
Abstract Coordinated control of structural accuracy and mechanical properties is the key to composites manufacturing and the prerequisite for aerospace applications. In particular, accurate and efficient prediction of curing-induced deformation (CID) is of vital importance for fiber reinforced polymer composites quality control. In this study, we explored a novel spatio-temporal prediction model, which incorporates the finite element method with a deep learning framework to efficiently forecast the curing-induced deformation evolution of composite structures. Herein, we developed an integrated convolutional neural network (CNN) and long short-term memory (LSTM) network approach to capture both the space-distributed and time-resolved… More >
Login
Register
