Rapid solving model for lattice mechanical properties based on CNN-GRU algorithm

To enhance the efficiency of solving mechanical properties of lattice materials, this paper constructs a rapid-solving model based on the CNN-GRU algorithm. Initially, methods for constructing the mathematical model of lattice units are investigated, and the equivalent Young’s modulus, shear modulus, and Poisson’s ratio are derived using the asymptotic homogenization theory. Subsequently, a voxel model based on the lattice structure is established, and a hybrid CNN-GRU model is developed to achieve rapid solving of key mechanical properties. Finally, the accuracy and efficiency of the model are verified. The results indicate that the CNN-GRU model significantly surpasses traditional finite element methods in computational efficiency, achieving a solution accuracy exceeding 92 %, thereby demonstrating the model’s effectiveness and adaptability. This research provides a novel approach for the design and optimization of lattice materials and contributes to the advancement of additive manufacturing technologies in material applications.