Mechanical Metamaterials by Topology Optimization

Mechanical Metamaterials by Topology Optimization

Blokland, Geert (TU Delft Mechanical, Maritime and Materials Engineering; TU Delft Precision and Microsystems Engineering)

Langelaar, M. (graduation committee)
Koppen, S. (graduation committee)

Delft University of Technology

Mechanical Engineering | Precision and Microsystems Engineering

2019-12-04

Auxetic materials exhibit material properties, which are usually not seen in nature. This type of materials belong to the class of mechanical metamaterials and can be used for e.g. energy absorption, cloaking of objects, shape morphing applications and the design of fiber-reinforced composites. They exhibit a negative Poisson’s value and derive their unusual properties from their architecture and are arranged in a pattern of unit cells. However, the design of their architecture is limited by the combination of degrees of freedom and therefore, a topology optimization (TO) procedure is utilized to allow sufficient design freedom. This thesis focuses on the generation, numerical and experimental validation of mechanical metamaterials. Auxetic unit cells are generated using an energy-based TO approach with periodic boundary conditions, with a valid response in the linear elastic regime. A patch of unit cells is numerically investigated for suitable test conditions and auxetic designs are fabricated for testing purposes using the fused deposit modeling (FDM) technique. The possibilities and shortcomings of this print technique are explored and relevant findings came out. Finally, compression tests of the as-printed auxetic designs are conducted to validate the auxetic behavior in practice. This thesis shows that the experimentally tested novel auxetic designs generate new knowledge towards the validation of mechanical metamaterials. It has been shown that the upcoming and user-friendly additive manufacturing technique, (FDM), is suited to generate and validate optimized geometries.

mechanical metamaterials
Topology Optimization
Additive Manufacturing
Experimental validation

http://resolver.tudelft.nl/uuid:49a9d185-6889-46f2-90dd-7e3fbfe0a392

Student theses

master thesis

© 2019 Geert Blokland