... dependence on governing equations and the complexity of mathematical operations. Herein, a data-driven method, named data-driven stochastic averaging, is developed to automatically discover the low-dimensional stochastic differential equations using only the random state data captured from the original high...

...Xu Guo; Zongliang Du; Chang Liu; Shan Tang In this article, a new uncertainty analysis-based framework for data-driven computational mechanics (DDCM) is established. Compared with its practical classical counterpart, the distinctive feature of this framework is that uncertainty analysis...

...Hang Yang; Hai Qiu; Qian Xiang; Shan Tang; Xu Guo In this paper, a data-driven approach for constructing elastoplastic constitutive law of microstructured materials is proposed by combining the insights from plasticity theory and the tools of artificial intelligence (i.e., constructing yielding...