Silicon based power semiconductors have long been used as the standard in ‘semiconductor technology in power conversion applications’. Recent developments replaces the Silicon with Silicon Carbide as it results in superior performance of the power conversion applications. However, due to the increased performance, challenges regarding heat dissipation emerge and the lifetime of the power semiconductor packaging or power module is compromised. Since this leads to an increase power density, the cooling of the power module is becoming of more importance and the heat sink becomes an interesting component to optimize. The best performance of a heat sink can be obtained when the flow through the device is turbulent. Developing turbulent flow heat sinks by using topology optimization methods can significantly improve the cooling performance compared to the current designs. This work is thus aimed towards improving methods for topology optimization of turbulent flow cooling devices. However, this work focuses on turbulent flow topology optimization only and aims to improve the accuracy of current methods. It is important that the flow physics are accurate since the thermal energy transfer is dependent on the flow field. The current state-of-the-art method based on the 𝑘−𝜔 turbulence model developed by Dilgen et al. is investigated. A design domain is subdivided into elements since the finite element method (FEM) is used, such that an optimization algorithm is able to turn every element into either fluid or solid with the goal of finding the best performing structure. This density based approach, models the solid domain as a highly impermeably porous material. To inhibit flow in the solid domain a Darcy penalization is added to the momentum equation. Moreover, in the method by Dilgen et al. boundary conditions in the other turbulent fields are also enforced using a similar penalization approach. Weaknesses and errors in the density based method are investigated by comparing solutions to ones computed on a body fitted mesh. It has been found that the largest errors in the solution, by using the state-of-the-art method, appear at the solid/fluid interface in the design. In these regions the penalizations are not applied correctly for the desired boundary conditions. Therefore, in this work it is improved on by the enforcement of the boundary condition by using the Dilation method. The Dilation method focuses on the solid/fluid region where it shifts the boundary conditions for the specific dissipation rate (𝜔) and ensures it reaches the desired value at the solid/fluid interface. Secondly, severe flow leakage is found in the “porous” solid domains using the state-of-the-art method. Flow leakage is reduced by using an improved formulation of the maximum Darcy penalization in the solid domain. Finally, the improved approach is investigated in several topology optimization cases and compared to the state-of-the-art Dilgen method. It is shown that by using the new approach, different designs with a better accuracy can be obtained. In an extreme test case, the Dilgen method resulted in an infeasible design which disconnects the flow inlets from the outlets while the new and improved method resulted in a feasible design.

The use of passive viscoelastic damping and active piezoelectric damping in a hybrid side-by-side configuration is explored in this paper. The goal is to combine the strengths of both individual methods to achieve better damping performance when targeting a single eigenmode or multiple resonances. It is found that a hybrid configuration where a passive constrained layer element covers the strain peak of a mode, with a active element placed next to it performs better than a passive or active damping treatment of the same size. It is more robust and uses lower control gains than active vibration control, and changes the system dynamics less than passive methods.

Topology optimization is a valuable tool for the optimization of all kinds of structures. It can create highly efficient but complex designs. This complexity can make these structures challenging to clean. However, cleanability is often a requirement in, for example, the medical or food industries. Currently, no method exists to reduce the complexity and create these cleanable structures using topology optimization. The goal of this project is to create a method that can generate two-dimensional cleanable structures. In this context, cleanability has been defined using two requirements. Every section of the surface must be visible, and no sharp edges can appear on the exterior. These requirements are met by generating a structural and cleanable shell around the design. The shell needs to be optimized to minimize the compliance of the entire structure. The addition of this shell has been achieved by the use of a hybrid method. This method combines two structural optimization methods, a level-set method, and the modified SIMP approach. The level-set method acts as a shape optimization method. Its shape forms a boundary in which the modified SIMP method is used to generate a design. Material is placed at this boundary of the level-set shape to create a shell that encloses the structure. Experiments on several sets of boundary conditions show a successful creation of a shell in every case. The resulting designs are not guaranteed to be cleanable, but a satisfactory result has been achieved in every case by changing some parameters. This method sets the stage for further development toward the application of topology optimization to create cleanable designs.

In this 3D fracture-based topology optimization framework, the author extended the 2D framework on tailoring fracture resistance for brittle materials (Zhang et al., 2022) to 3D. In the optimization, the topology is described by radial basis functions interpolated level set function, and the problem is solved by the Interface-enriched Generalized Finite Element Method (IGFEM). Cracks are assumed to exist on enriched nodes that are added on the boundary of the geometry to increase the accuracy of approximation. The first part of the work assumes cracks to be semi-circular with the crack plane perpendicular to the boundary, and the crack opening direction to be either parallel to the KM- or LM-plane of the global coordinates. An extended framework that assumes crack opening direction perpendicular to the surface first principal stress is also developed at the end. The energy release rates (ERRs) of the cracks are evaluated with the topological derivative method, which requires only a stress field of the geometry and weight functions that relate the stress and stress intensity factors (SIFs). The weight functions are found by a finite element analysis on a cuboid with a crack. This approach is computationally efficient because it eliminates the need of actually modeling and meshing the crack planes in the geometry during optimization. Moreover, a 3D stress recovery technique (or stress improvement procedure, SIP) is used to recover the nodal stress non-locally to improve the accuracy. The objective function is then established with the ]-mean aggregation of the ERRs. Finally, Numerical examples in 3D, including the famous L-bracket benchmark problem, are performed to prove the correctness and capacity of the framework. In conclusion, this extended framework shows more flexibility and provides more information to the optimized design than the 2D framework by considering an added dimension both in analyzed geometry and crack shape, i.e., the effect of the anisotropy of cracks can be captured.

The goal of this thesis is to look into the possibilities of making origami neutrally stable. This is wanted because the inherent stiffness of origami mechanisms introduces unwanted artifacts such as a higher actuation force, and the mechanism not following the theoretical kinematics. By making an origami mechanism neutrally stable the inherent stiffness of the pattern can be removed, and with that the unwanted artifacts as well. Two different strategies are explored, both a form of static balancing. With static balancing, two elements are balanced against each other. In the origami application, this means that two creases are balanced against each other. For the first strategy, a negative stiffness crease is combined with a positive stiffness crease. And for the second strategy two equal but opposite constant moment creases are balanced. To achieve this a negative stiffness, or constant moment crease needs to be designed. For the negative stiffness crease, a design was made where a flat sheet with a slot in the middle was prestressed into a saddle form. This showed bi-stable behavior, and with that negative stiffness. The range of negative stiffness was too short to be relevant for origami. And the prestressing proved hard to model. For the constant moment crease, a convex crease was designed, which did not need to be prestressed. This was easier to model, and three different geometries were found that showed a constant moment. By optimizing these geometries a constant moment over a range of 80 degrees was found. To check if the model is correct, a prototype experiment was performed. The optimized geometry was 3D printed and tested under the same boundary conditions that were present in the model. The results of the prototype experiment matched the results of the model, thereby validating it.

Power electronic systems are reaching higher efficiencies as their technology advances, which often results in components of smaller size with higher power densities. Cooling these components becomes increasingly challenging as high power densities require cooling with large heat fluxes. Topology optimization (TO) of thermo-fluids can be used to find cooling interface geometries which achieve high heat transfer with realistic pumping power. However, current methods for thermo-fluid TO show several issues. Firstly, the fluid models used for thermo-fluid TO show weaknesses that cause deviating behavior compared to conventional fluid models, which can result in large under- or overestimation of heat transfer especially when applied to turbulent flow. Secondly, although this deviating behavior is known to result in inferior modeling accuracy, the achievable accuracy of thermo-fluid TO has never been quantified. Lastly, TO currently requires many modeling parameters to be specified manually. Since these parameters largely affect the accuracy of the thermo-fluid solver, tedious parameter tuning is part of the TO design process. This thesis firstly presents a framework which allows quantitative analysis of the modeling accuracy achievable with density-based thermo-fluid models in 2D. The framework reveals several effects causing errors in turbulent flow, as well as a predictability of density-based boundary layer flows. Secondly, a method is tested which minimizes errors of the density-based thermo-fluid models by meta-optimizing the modeling parameters. Applied to a test-case with turbulent flow, this method achieves up to 27% reduction of the modeling error compared to a parameter sweep. When applied to a laminar TO, it achieves similar accuracy as a manually tuned TO without needing any tuning. A second mitigation method which adjusts the thermal conductivity of porous solid material to compensate for erroneous convective heat transfer is infeasible, as it provides less accurate results than the first method. Lastly, a post-processing method which uses the meta-optimized data is tested and found to provide better accuracy than a conventional post-processing method.