Deep learning is known as one of the most popular fields and drawing much attention of many researchers. It is widely used in many fields both academia and industry such as computer vision and pattern recognition , natural language processing, machine health monitoring, bankruptcy prediction, fault-tolerant control, structural engineering, material design , etc. Therefore, we investigate deep learning for structural analysis to save computational cost.

Papers

1. T.N. Nguyen, S. Lee, H. Nguyen-Xuan, J. Lee. A novel analysis-prediction approach for geometrically nonlinear problems using group method of data handling. Computer Methods in Applied Mechanics and Engineering 354, 506-526. (2019) (link)

2. T.N. Nguyen, H. Nguyen-Xuan, J. Lee. A novel data-driven nonlinear solver for solid mechanics using time series forecasting. Finite Elements in Analysis and Design 171, 103377 . (2020) (link)