Functionally graded lattice structure topology optimization for the design of additive manufactured components with stress constraints

By Lin Cheng, Jiaxi Bai, Albert C. To. Computer Methods in Applied Mechanics and Engineering, 2019

268 citations recorded by the source corpus.

Abstract Advances in additive manufacturing (AM) have drawn considerable interest due to its ability to produce geometrically complex structure, such as lattice materials. In this work, a novel methodology is proposed to design graded lattice structure through topology optimization under stress constraint, in order to generate lightweight lattice structure design with predictable yield performance. Instead of using the power law of material interpolation in the SIMP method, asymptotic homogenization method is employed to compute the effective elastic properties of lattice material in terms of design variable, i.e. relative density. For yield strength, a multiscale failure model is proposed to capture yield strength of microstructure with macroscopic stress. At macroscale, a modified Hill’s yield criterion is employed to describe anisotropic yield strength of lattice material. The material constants in Hill’s model are assumed to be a function of relative density, and thus a model is built up to formulate yield strength of lattice structure with macroscopic stress. The experimental verification on the printed samples demonstrates that both the homogenized elastic model and yield model can accurately describe the elasticity and plasticity of the lattice structure. Based on the proposed material interpolation for lattice structure, a lattice structure topology optimization framework is proposed for minimizing total weight of the structure under stress constraint. The sensitivity analysis is performed for the implementation of the optimization algorithm. Two three-dimensionally numerical examples are performed to demonstrate the effectiveness of the proposed optimization method, as well as accuracy of the proposed homogenization technique for graded lattice structure design. Experiment is conducted to systematically examine yielding of the optimally graded lattice structure design and compare its performance with a uniform structure. It is found that the proposed optimization framework is valid for the design examples examined and can significantly enhance mechanical performance of the structure (i.e. yield loading, stiffness, energy absorption, etc.)

Subfields: Civil and Structural Engineering, Mechanics of Materials

View Paper: https://www.semanticscholar.org/paper/552aed10c8541ccfe777920cbbe4609af8f0a93d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. Lin Cheng
2. Jiaxi Bai
3. Yu-Chin Chan
4. Ping Zhu
5. Wei Chen
6. Faez Ahmed
7. Zhao Liu
8. Liwei Wang

In Mechanics of Materials

1. Jiaxi Bai
2. Yu-Chin Chan
3. Ping Zhu
4. Wei Chen
5. Lin Cheng
6. J. Lemon
7. Liwei Wang
8. Qiang Chen

Citations in the corpus

• On utilizing topology optimization to design support structure to prevent residual stress induced build failure in laser powder bed metal additive manufacturing (2019, background): “More details about these two matrixes refer to [71].”
• Deep Generative Modeling for Mechanistic-based Learning and Design of Metamaterial Systems (2020, background): “With the growth of data resources [18], a promising direction is to generate a database of the metamaterial microstructures and then utilize it to enable efficient data-driven design of a heterogeneous system [19-28].”