... (LSTM) deep learning method, and theoretical modeling was proposed to investigate the impact of the sewing position on the harvest performance of the FPEH, utilizing real three-dimensional heart deformation data as the end-to-end displacement load for the FPEH. The results reveal that the sewing...

... orientation distribution (FOD) in a prepreg platelet molded composite (PPMC) plate. MR-AI approach uses thermal strain components on the surfaces of a PPMC plate as input to the deep learning model, which allows to predict a distribution of local through-thickness average fiber orientation state in the entire...

.... H. , and Buehler , M. J. , 2021 , “ Deep Learning Model to Predict Complex Stress and Strain Fields in Hierarchical Composites ,” Sci. Adv. , 7 ( 15 ). 10.1126/sciadv.abd7416 [41] Hsu , Y. C. , Yu , C. H. , and Buehler , M. J. , 2020 , “ Using Deep Learning to Predict...

... 09 2021 SuperMeshing metal forming physical fields deep learning attention mechanism Numerical methods, for instance, finite element method (FEM), are widely used in the engineering domain [ 1 , 2 ] for quantitative solutions. Compared with the traditional experimental approaches...

.... , Chen , W. , Ehmann , K. , Cao , J. , and Bessa , M. A. , 2019 , “ Deep Learning Predicts Path-Dependent Plasticity ,” Proc. Natl. Acad. Sci. U. S. A. , 116 ( 52 ), pp. 26414 – 26420 . 10.1073/pnas.1911815116 [24] Koeppe , A. , Bamer , F. , and Markert , B...

...Haoliang Jiang; Zhenguo Nie; Roselyn Yeo; Amir Barati Farimani; Levent Burak Kara Using deep learning to analyze mechanical stress distributions is gaining interest with the demand for fast stress analysis. Deep learning approaches have achieved excellent outcomes when utilized to speed up stress...