Topology optimization has seen increased interest with the rise of additive manufacturing (AM) as a fabrication method, because of its ability to exploit the geometric complexity that AM offers. However, AM still imposes some geometric restrictions on the design, most notably on minimum feature size, overhang angles, and enclosed voids. Enclosed voids are problematic because for many AM methods it is impossible to remove supports, unmelted powder or uncured liquid from them. This paper introduces a filter based on a cumulative sum flood fill algorithm to alleviate this issue in a flexible manner. This filter produces a density field where every enclosed void element is rendered solid. It successfully eliminates enclosed voids in both 2D and 3D problems, with low computational cost due to its geometric nature. In addition we demonstrate direct control over the location, amount, and size of powder removal features by varying boundary conditions for the filter, running additional flood fills, and adding morphology operators, respectively.

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The design of high-performance mechatronic systems is very challenging, as it requires delicate balancing of system dynamics, the controller, and their closed-loop interaction. Topology optimization provides an automated way to obtain systems with superior performance, although extension to simultaneous optimization of both topology and controller has been limited. To allow for topology optimization of mechatronic systems for closed-loop performance, stability, and disturbance rejection (i.e. modulus margin), we introduce local approximations of the Nyquist curve using circles. These circular approximations enable simple geometrical constraints on the shape of the Nyquist curve, which is used to characterize the closed-loop performance. Additionally, a computationally efficient robust formulation is proposed for topology optimization of dynamic systems. Based on approximation of eigenmodes for perturbed designs, their dynamics can be described with sufficient accuracy for optimization, while preventing the usual threefold increase of additional computational effort. The designs optimized using the integrated approach have significantly better performance (up to 350% in terms of bandwidth) than sequentially optimized systems, where eigenfrequencies are first maximized and then the controller is tuned. The proposed approach enables new directions of integrated (topology) optimization, with effective control over the Nyquist curve and efficient implementation of the robust formulation.

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High-precision motion systems are crucial for many applications, such as in semiconductor equipment, microscopy, robotics, and medical devices. Next to high operating speeds, high accuracy and precision are required, which makes the design of these systems a challenging task. Dynamics, feedback control, and their interaction all play an important role in the design and its final performance. This thesis shows that topology optimization in combination with additive manufacturing offers new opportunities for the automated design of motion systems with unprecedented performance. The first challenge addressed is the manufacturability of the designs, for which a systematic optimization setup is presented allowing directly producible designs. This is verified by manufacturing and testing an optimized design. Furthermore, the computational time required for full-scale topology optimization is reduced significantly, by using reduced-order models and approximation of design sensitivities. Thirdly, effective optimization formulations are introduced that allow combined optimization of topology and controller for closed-loop performance, such as bandwidth, closed-loop stability, and disturbance rejection properties. Combining all these techniques, this thesis demonstrates that it is possible to perform integrated controller-structure topology optimization of motion systems of industry-relevant complexity.@en

The design of high-precision motion stages, which must exhibit high dynamic performance, is a challenging task. Manual design is difficult, time-consuming, and leads to sub-optimal designs that fail to fully exploit the extended geometric freedom that additive manufacturing offers. By using topology optimization and incorporating all manufacturing steps (printing, milling, and assembly) into the optimization formulation, high-quality optimized and manufacturable designs can be obtained in an automated manner. With a special focus on overhang control, minimum feature size, and computational effort, the proposed methodology is demonstrated using a case study of an industrial motion stage, optimized for maximum eigenfrequencies. For this case study, an optimized design can be obtained in a single day, showing a substantial performance increase of around 15% as compared to a conventional design. The generated design is manufactured using laser powder-bed fusion in aluminum and experimentally validated within 1% of the simulated performance. This shows that the combination of additive manufacturing and topology optimization can enable significant gains in the high-tech industry.

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In many engineering applications, the dynamic frequency response of systems is of high importance. In this paper, we focus on limiting the extreme values in frequency response functions, which occur at the eigenfrequencies of the system, better known as resonant peaks. Within an optimization, merely sampling the frequency range and limiting the maximum values result in high computational effort. Additionally, the sensitivities of this method are not complete, since only information about the resonance peak amplitude is included. The design dependence with respect to the frequency of the extreme value is missed, thus hampering the convergence. To overcome these difficulties, we propose a constraint which can efficiently and accurately limit resonant peaks in a frequency response function. It has a close relation with eigenfrequency maximization; however, in that case, the amplitudes of the frequency response are unconstrained. In order to keep the computational time low, efficient implementation of this constraint is studied using reduced-order models based on modal truncation and modal truncation augmentation. Furthermore, approximated sensitivities are investigated, resulting in a large computational gain, while still yielding very accurate sensitivities and designs with almost equivalent performance compared with the non-approximated case. Conditions are established for the accuracy and computational efficiency of the proposed methods, depending on the number of peaks to be limited, numbers of inputs and outputs, and whether or not the system input and output are collocated.@en

In the design process of high-precision motion stages, the dynamic behavior is of paramount importance. Manual design of such a stage is a time-consuming process, involving many iterations between engineers responsible for mechanics, dynamics and control. By using topology optimization in combination with additive manufacturing, post-processing using traditional machining and parts assembly, it is possible to arrive at an optimal design in an automated manner. The printing, machining, and assembly steps are incorporated in the optimization in order to directly arrive at a manufacturable design. With a motion stage demonstrator optimized for maximum eigenfrequencies, it is shown that combining additive manufacturing and topology optimization at industry-relevant design precision is within reach and can be applied to high-performance motion systems.@en

A great deal of engineering effort is focused on changing mechanical material properties by creating microstructural architectures instead of modifying chemical composition. This results in meta-materials, which can exhibit properties not found in natural materials and can be tuned to the needs of the user. To change Poisson's ratio and Young's modulus, many current designs exploit mechanisms and hinges to obtain the desired behavior. However, this can lead to nonlinear material properties and anisotropy, especially for large strains. In this work, we propose a new material design that makes use of curved leaf springs in a planar lattice. First, analytical ideal springs are employed to establish sufficient conditions for linear elasticity, isotropy, and a zero Poisson's ratio. Additionally, Young's modulus is directly related to the spring stiffness. Second, a design method from the literature is employed to obtain a spring, closely matching the desired properties. Next, numerical simulations of larger lattices show that the expectations hold, and a feasible material design is presented with an in-plane Young's modulus error of only 2% and Poisson's ratio of 2.78×10^-3. These properties are isotropic and linear up to compressive and tensile strains of 0.12. The manufacturability and validity of the numerical model is shown by a prototype.

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A zero free length (ZFL) spring is a spring with special properties, which is commonly used in static balancing. Existing methods to create ZFL springs all have their specific drawbacks, which rises to the need of a new method to create such a spring. A method is proposed to design planar ZFL springs with specified stiffness (250–750 N/m) within a certain range (up to 20 mm of displacement). Geometric non-linearities of a curved leaf spring are exploited by changing its shape. The shape is determined by a non-linear least squares algorithm, minimizing the force residuals from a non-linear numerical analysis. Constraints are introduced to help in preventing the spring from intersecting itself during deformation. For three types of springs with different boundary conditions, designs are found with characteristic shapes and maximum force errors less than 1%. A trend is observed between spring size, maximum stress and desired stiffness. New type of ZFL springs can now be designed, which can not only be used in existing applications, but also enables the use of ZFL springs in micro mechanisms.@en