This presentation was made at CAASE18, The Conference on Advancing Analysis & Simulation in Engineering. CAASE18 brought together the leading visionaries, developers, and practitioners of CAE-related technologies in an open forum, to share experiences, discuss relevant trends, discover common themes, and explore future issues.
For the past three decades, topology optimization has been remarkably popular in the engineering design community due to its capability on designing lightweight structures by optimally distributing materials to carry loads. Recent research trends in topology optimization include multidisciplinary optimization, hierarchical distributed computing, and various manufacturing method-oriented design. In particular, generating lightweight designs that can be producible by various manufacturing methods is critically important in industry. These include various manufacturing methods, such as minimum/maximum member size, various symmetry, extrusion, casting, milling, and 3D printing.
In particular, 3D printing, or additive manufacturing, becomes an emerging technology as it allows manufacturing complex shapes that were not possible in conventional subtractive manufacturing technologies, such as milling. The current research trend in topology optimization for additive manufacturing focuses on how to design a structure so that the amount of supporting materials can be reduced or removed. However, the technology still remains in the regime of producing solid, isotropic materials. Due to remarkable advances in the additive manufacturing technology, it is now possible to build lattice structures, which involve repetitive patterns of a particular cell shape or type. In fact, lattice structures can be a unique feature for additive manufacturing. It has been demonstrated that lattice structures can reduce the structural weight with the same functionality as with homogeneous materials. Conventional topology optimization is too restrictive since it cannot create intricate microstructures as provided by a lattice solution.
The objective of this work is to seamlessly integrate the concept of lattice structure with topology optimization. First, 16 different shapes/patterns of lattice structures are modeled using representative volume elements (RVEs). The behavior of a lattice structure is homogenized using an anisotropic material. This is a similar concept used in composite materials and multiscale modeling. The stiffness of a lattice structure is a function of the diameter of beams that composed of the lattice structure. The volume fraction of lattice structure can be changed as the diameter of beams changes. Since the volume fraction changes during topology optimization, it would be important to make a relationship between the volume fraction and the stiffness of a lattice structure. We utilize a polynomial response surfaces for this relationship. Two possible integration strategies will be discussed. The first strategy is to replace the void region in topology optimization with lattice structures, while the second is to replace the solid region to lattice structures.
|Date||6th June 2018|