... the predictive limit of the model. We conclude the paper with a discussion on limitations and possible next steps. One of the challenging aspects of applying deep learning to mechanics is to expand models beyond relatively simple interpolation solutions or “curve fitting” to make predictions for scenarios...

... that deep learning based approaches have become the dominant position since the advance of convolution neural network for processing image. Meanwhile, the attention mechanism that used in CNN achieves outstanding performance. This trend also shows in finite element analysis topics. Therefore, we review four...

... by the Applied Mechanics Division of ASME for publication in the J ournal of A pplied M echanics . 24 03 2021 07 05 2021 07 05 2021 26 05 2021 deep learning viscoplastic behavior plasticity history LSTM network memory data-driven modeling computational mechanics...

...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...