Topology Optimization for 4D-Printed Structures

Master thesis (2021)

Authors

S.A. Pakvis Mechanical Engineering

Contributors

Matthijs Langelaar Computational Design and Mechanics - Mechanical, Maritime and Materials Engineering (supervisor 1)
R.A.J. van Ostayen Mechatronic Systems Design - Mechanical, Maritime and Materials Engineering (supervisor 2)
S. Koppen Computational Design and Mechanics - Mechanical, Maritime and Materials Engineering (supervisor 2)
Giulia Scalet Pavia University (supervisor 2)
Faculty
Mechanical Engineering
Copyright: © 2021 Sara Pakvis
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Published Date

03-03-2021

Language

English

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Faculty

Mechanical Engineering

Abstract

In recent developments in the field of multi-material additive manufacturing, differences in material properties are exploited to create printed shape memory structures, which are referred to as 4D-printed structures. New printing techniques allow for the introduction of prestresses in the specimen during manufacturing. This research focuses on bi-polymer 4D-printed structures, where the transformation process is based on a heat-induced stiffness transition in one of the materials and an initial prestress in the other material. Upon the decrease in stiffness, the prestress is released, causing a bending behaviour. A methodology to find the design of 4D-printed structures is developed, where a finite element model is combined with a density-based topology optimization method to describe the material layout. This modeling approach is verified by a convergence analysis and validated by comparing its numerical results to analytical and published data. The use of topology optimization to design 4D-printed structures is explored by applying the methodology to a variety of design problems. Bi-layer designs are printed with acrylonitrile butadiene styrene (ABS) and thermoplastic polyurethane (TPU), of which the latter material is prestressed during the Fused Filament Fabrication (FFF) printing process. Tests are performed with these printed samples, with the goal to find the prestress value and to further validate the modeling approach by comparing the numerical results to the experimental results. Once the prestress value is found, topology optimized samples are printed and tested to evaluate their performance.