Data-driven design of graded composite lattice structures with multiple microstructure prototypes and materials

Abstract

Lattice structures have attracted much attention from engineers due to their excellent properties, especially with the rise of additive manufacturing technology. In this paper, a homogenization-based data-driven optimization method is proposed for designing graded composite lattice structures composed of a series of composite lattice microstructures generated from different microstructure prototypes, which are represented by using corresponding basic level set functions. Using different cutting planes to cut the same basic level set function can obtain a series of basic microstructures with different relative densities and similar configurations. The composite lattice microstructures can be obtained by combining the basic microstructures generated from different basic level set functions. The homogenization approach is used to calculate the equivalent elasticity matrix of the composite lattice microstructure. The mapping relationships among its density, equivalent elasticity matrix, and the height of cutting plane are established. Numerical examples of both compliance minimization and frequency maximization problems are conducted to verify the validation and effectiveness of the proposed method. • Homogenization-based data-driven optimization method for designing graded composite lattice structures is developed. • The mapping relationships among the relative density, the equivalent elastic tensor, and the height of cutting plane are established based on the homogenization theory. • The composite lattice microstructure is composed of several basic microstructures generated from corresponding microstructure prototypes. • Both the compliance minimization and the frequency maximization problems are conducted.