Design of fabric rubber composite seals with multilevel structure using machine learning method

The multilevel structure of the fabric and rubber in the fabric rubber composite seals makes it challenging to design the mechanical properties and the seal performance of the seal structure efficiently and accurately. In the present work, a machine learning framework is proposed to predict the sealing performance, as well as the mechanical properties, of fabric rubber composite seal combining the finite element and artificial intelligence methods. First, the input dataset is generated by establishing the finite element models considering the woven form of the fabric and the anisotropic hyperelastic behavior of the fabric rubber composites. Second, the dataset obtained by simulation is utilized to train, validate, and evaluate the artificial neural network. Finally, the trained network is well evaluated using the experimental and simulation results. The proposed machine learning framework provides the possibility to link the macroscopic performance with multilevel structures of composite materials, and demonstrates the applicability to predict the property-performance relationship of complex materials with multilevel structures.