From 3D Models to 3D Prints: an Overview of the Processing Pipeline

Due to the wide diffusion of 3D printing technologies, geometric algorithms for Additive Manufacturing are being invented at an impressive speed. Each single step, in particular along the Process Planning pipeline, can now count on dozens of methods that prepare the 3D model for fabrication, while analysing and optimizing geometry and machine instructions for various objectives. This report provides a classification of this huge state of the art, and elicits the relation between each single algorithm and a list of desirable objectives during Process Planning. The objectives themselves are listed and discussed, along with possible needs for tradeoffs. Additive Manufacturing technologies are broadly categorized to explicitly relate classes of devices and supported features. Finally, this report offers an analysis of the state of the art while discussing open and challenging problems from both an academic and an industrial perspective.Comment: European Union (EU); Horizon 2020; H2020-FoF-2015; RIA - Research and Innovation action; Grant agreement N. 68044

Optimal Grading for Strength and Functionality of Parts Made of Interpenetrating Polymer Networks: Load Capacity Enhancement

Uniform parts with stress concentrations or singularities are prone to failure under relatively small loads, which motivates researchers to seek methods to enhance the strength of these parts. This dissertation studies the optimization of material grading to design parts made of functionally graded interpenetrating polymer networks (FG-IPNs) to improve their load capacity. An acrylate/epoxy IPN with variations of elastic Young’s modulus, Poisson’s ratio, and ultimate stress at failure is used for optimization of a plate with stress concentration. The grading is optimized by attaching the finite element method (FEM) solver to a general purpose bound-constrained optimizer. Two examples, a plate with a hole and a bent bracket, show more than 100% improvement in the part’s load capacity when compared to the uniform IPNs. Parts with stress singularities are studied using a PMMA/PU IPN system. For this system, we have the elastic modulus and the critical stress intensity factor KIC as a function of the concentration of the components. A material mesh is utilized to control the grading near the crack tip and uniform material is assumed outside the tip area. The displacement correlation technique (DCT) is used to calculate stress intensity factors and the maximum hoop stress criterion is selected as the fracture criterion. Parts with edge cracks, interior cracks and interacting cracks under tension are considered. For the PMMA/PU IPN system, improvements in load capacity in the order of one hundred percent were commonly obtained through grading the region around the crack tip, compared to both optimal uniform plates, and plates with simple toughening of the region around the crack. In addition, in FEM modelling of FGM part with graded elements, the polynomial interpolations used in such elements can be prone to oscillations that can result in regions of negative elastic modulus, even with only positive nodal values of elastic moduli. The result of these negative modulus regions, even if the region is small, can be unexpected singularities in the solution. To avoid this potential problem, conditions for robust higher order materially graded elements were developed. Advisor: Mehrdad Negahba

Embedded thick-film resistors applied in low temperature co-fired ceramic circuit substrates

The materials that are used to create low temperature co-fired ceramics (LTCC) circuits (produced from green tape and various pastes) can be processed by the equipment of the conventional thick-film technology (screen printing machine, drying and burning ovens). The equipment needed to produce multilayer boards (sinter press, tools, punching machine or Nd-YAG laser) can be purchased with a little investment. At the same time the high temperature co-fired ceramics (HTCC) technology requires completely new equipment, so the changeover is harder and more expensive. An LTCC test-circuit was designed and realized by using the thick-film technology equipment at the Department of Electronics Technology, BME. The surface and embedded resistors were made from thick-film paste. In the course of the realization and with circuit measurements it could be determined what have to be considered at the pre-calculation of the resistor values

Fabrication of Wet-Responsive Bioinspired Adhesives and Their Applications

Department of Mechanical EngineeringInspired by the fascinating adhesion properties of various creatures in nature, various bioinspired adhesives have been developed. Since the bioinspired adhesives exhibit excellent adhesion strength and reversible adhesion, they have strong potential for a wide variety of applications including wearable devices, nanoscale manufacturing techniques, and soft robotics. However, the bioinspired adhesives made of conventional elastomeric materials have limited adhesion strengths to rough surfaces and limited controllability on adhesion strengths, which limits their practical applications. As the challenges mainly result from the fixed physical property (e.g. elastic modulus of material) of the elastomer-based adhesives, utilization of stimuli-responsive materials that enable active modulation of their mechanical properties on demand is expected to be an effective solution overcoming the limitations. Wet-responsive hydrogels are tunable in their shape, volume, and mechanical properties based on hydration/dehydration in an active and reversible manner. Therefore, it is expected that bioinspired adhesives made of the wet-responsive hydrogels could overcome the aforementioned challenges. In this dissertation, we propose wet-responsive bioinspired adhesives made of hydroxypropyl cellulose (HPC) hydrogel and polyethylene dimethacrylate (PEGDMA) hydrogel that exhibit superior surface adaptability and high adhesion-on/off switchability, respectively. For superior adaptability, a bioinspired adhesive comprised of wet-responsive HPC is proposed as it enables adaptation to a rough surface due to its controllable swelling behavior. By hydration/dehydration, the elastic modulus of the HPC hydrogel can be modulated on demand. In the presence of a small amount of water, the individual bioinspired HPC microstructures in the adhesive can be easily deformed along the rough surface with the decreased elastic modulus of the HPC. As dehydrated, the elastic modulus of HPC microstructures is recovered with maintaining the deformed morphology. Through these processes, the surface roughness-adapted HPC adhesive exhibits strong adhesion strength. Furthermore, the adaptable HPC adhesive is reusable as the deformed microstructures can recover their original shapes based on a shape-memory capability of HPC. In order to develop the bioinspired adhesive that exhibits actively controllable and switchable adhesion on demand, PEGDMA hydrogel with swelling behavior is utilized as it has shape-reconfigurable property. The prepared PEGDMA adhesive shows high adhesion strengths against substrates with the aid of bioinspired nano??? or microstructure array in the dry state (adhesion-on state). When the adhesive is exposed to water, a hydration???induced shape transformation of the array and macroscopic film bending occur, switching the adhesion off with an extremely high adhesion switching ratio. Also, the switchable adhesion behavior of the adhesive is maintained over repeating cycles of hydration and dehydration, indicating their ability to be used repetitively. As the rough surface adaptation and adhesion on/off properties of the developed adhesives only require water droplets, they have a wide range of applications in diverse fields. Specifically, the adhesives have a strong potential for use in a biomedical field as the HPC and PEGDMA hydrogels are biocompatible. Accordingly, we demonstrate several unique biomedical practical applications of the developed adhesives. Firstly, with the adaptable HPC adhesive, an attachable photonic skin is developed as a wearable skin-like sensor. The photonic skin consisting of an HPC mechanochromic sensor and the adaptable adhesive can firmly laminate to diverse substrates including human skins, detecting mechanical signals from various target objects. Secondly, the adhesion-switchable PEGDMA adhesive is utilized for a nanotransfer printing (nTP). We demonstrate that diverse metallic and semiconducting nanomembranes can be transferred from donor substrates to either rigid or flexible surfaces including biological tissues with the PEGDMA adhesive in a reproducible and robust fashion. In total, this dissertation presents the fabrication of wet-responsive bioinspired adhesives and their applications. The overall contents consist of three main themes, that are as follow: (1) fabrication of bioinspired adhesives with optimized geometries, (2) rough surface-adaptable adhesive made of wet-responsive HPC hydrogel and (3) adhesion-switchable adhesive made of wet-responsive PEGDMA hydrogel.clos

Back-Propagation Optimization and Multi-Valued Artificial Neural Networks for Highly Vivid Structural Color Filter Metasurfaces

We introduce a novel technique for designing color filter metasurfaces using a data-driven approach based on deep learning. Our innovative approach employs inverse design principles to identify highly efficient designs that outperform all the configurations in the dataset, which consists of 585 distinct geometries solely. By combining Multi-Valued Artificial Neural Networks and back-propagation optimization, we overcome the limitations of previous approaches, such as poor performance due to extrapolation and undesired local minima. Consequently, we successfully create reliable and highly efficient configurations for metasurface color filters capable of producing exceptionally vivid colors that go beyond the sRGB gamut. Furthermore, our deep learning technique can be extended to design various pixellated metasurface configurations with different functionalities.Comment: To be published. 25 Pages, 17 Figure

USING COMPUTATIONAL METHODS TO OPTIMIZE HIGH HEAT FLUX COMPONENT THERMAL PERFORMANCE IN MAGNETIC CONFINEMENT FUSION REACTOR RESEARCH

Heat transfer enhancement by means of internally modified geometries in tubes and channels is an important mechanism to improve the survivability of components in extreme high-heat flux environments. Various features such as ribs and fins are studied using computational fluid dynamics in both uniform and one-sided heating in tubes and rectangular channels respectively to determine the most effective geometries across a variety of different flow and heating conditions. This work examines heat transfer enhancement and rib geometry optimization to support experimental research for nuclear fusion applications. The project begins by designing and analyzing test sections supporting a helium flow loop assembled at Oak Ridge National Laboratory to analyze heat transfer enhancement for systems such as blanket and divertor components. This initial phase uses STAR-CCM+ to study a base set of literature-supported helium-cooled ribbed and fin geometries in tubes to examine their thermal and pressure drop performance relative to one another. The scope then broadens to using the STAR-CCM+ Design Manager tool to build a Pareto frontier of competing surface average Nusselt number and Fanning friction factor objectives. This study explores a variety of rib shapes and orientations in a rectangular air-cooled channel for optimal heat transfer performance and friction to determine the relationships between the different shapes, orientations, flow phenomena, and thermal performance due to the enhancements. Finally, this project concludes by using optimization techniques to perform single objective optimization of overall heat transfer enhancement on ribs in helium-cooled tubes for the helium flow loop conditions to improve knowledge surrounding geometry enhancement for fusion blanket research --Abstract, p. i

Aerodynamics of a squareback road vehicle with active flow control

1noL'abstract è presente nell'allegato / the abstract is in the attachmentopen678. INGEGNERIA MECCANICAnopartially_openembargoed_20211021Cerutti, JUAN JOS