Investigation into adaptive slicing methodologies for additive manufacturing

Adaptive slicing is a methodology used to optimise the trade-off between build-time reduction and geometric accuracy improvement in additive manufacturing (AM). It works by varying decreasing layer thickness in sections of high curvature. However, current adaptive slicing methodologies all face the difficulty of adjusting layer thickness precisely according to the variations of the model’s geometry, thereby limiting the geometric accuracy improvement. This thesis tackles this difficulty by indicating the geometric variations of the model by evaluating the ratio of the volume of each sliced layer’s geometric deviation to the volume of its corresponding region in the digital model. This indication is accomplished because all the topological information of the corresponding region is considered in assessing the geometric deviation (volume) between each sliced layer and its corresponding region. Through having this precise indication to modify each layer thickness, this thesis aims to develop an adaptive slicing that can mitigate geometric inaccuracies (e.g. staircase effect and dimensional deviation) while balancing the build time. This slicing is evaluated using six different test models, compared with three current slicing methodologies (voxelisation-based, cusp height-based, and uniform slicing), and validated through computation and manufacturing. These validations all demonstrate that volume deviation-based slicing optimises the trade-off between build-time reduction and geometric accuracy improvement better than the other existing slicing methodologies. For example, it can reduce the build time by nearly half compared to other existing slicing methodologies assuming a similar degree of printed parts’ geometric accuracy. The improved trade-off optimised by volume deviation-based slicing can directly benefit the AM applications in the aerospace and medical industries. This is because current research has shown geometric inaccuracies are the primary cause of reducing energy efficiency (e.g. turbine blade and wind tunnel testing models) and having failed implants (e.g. hip and cranial implants, dental prostheses). In addition to improving the geometric accuracy of AM-constructed parts, volume deviation-based slicing may also be incorporated with non-planar layer slicing. Non-planar layer slicing is designed to mitigate the mechanical anisotropy of printed parts by using curved-sliced layers. By integrating volume deviation-based slicing with non-planar layer slicing, the thickness of each curved-sliced layer can be adjusted according to the model’s geometric variations and, therefore, has a possibility of reducing the geometric inaccuracies and mechanical anisotropy simultaneously.Open Acces

CAVASS: A Computer-Assisted Visualization and Analysis Software System

The Medical Image Processing Group at the University of Pennsylvania has been developing (and distributing with source code) medical image analysis and visualization software systems for a long period of time. Our most recent system, 3DVIEWNIX, was first released in 1993. Since that time, a number of significant advancements have taken place with regard to computer platforms and operating systems, networking capability, the rise of parallel processing standards, and the development of open-source toolkits. The development of CAVASS by our group is the next generation of 3DVIEWNIX. CAVASS will be freely available and open source, and it is integrated with toolkits such as Insight Toolkit and Visualization Toolkit. CAVASS runs on Windows, Unix, Linux, and Mac but shares a single code base. Rather than requiring expensive multiprocessor systems, it seamlessly provides for parallel processing via inexpensive clusters of work stations for more time-consuming algorithms. Most importantly, CAVASS is directed at the visualization, processing, and analysis of 3-dimensional and higher-dimensional medical imagery, so support for digital imaging and communication in medicine data and the efficient implementation of algorithms is given paramount importance

How round is a protein? Exploring protein structures for globularity using conformal mapping.

We present a new algorithm that automatically computes a measure of the geometric difference between the surface of a protein and a round sphere. The algorithm takes as input two triangulated genus zero surfaces representing the protein and the round sphere, respectively, and constructs a discrete conformal map f between these surfaces. The conformal map is chosen to minimize a symmetric elastic energy E S (f) that measures the distance of f from an isometry. We illustrate our approach on a set of basic sample problems and then on a dataset of diverse protein structures. We show first that E S (f) is able to quantify the roundness of the Platonic solids and that for these surfaces it replicates well traditional measures of roundness such as the sphericity. We then demonstrate that the symmetric elastic energy E S (f) captures both global and local differences between two surfaces, showing that our method identifies the presence of protruding regions in protein structures and quantifies how these regions make the shape of a protein deviate from globularity. Based on these results, we show that E S (f) serves as a probe of the limits of the application of conformal mapping to parametrize protein shapes. We identify limitations of the method and discuss its extension to achieving automatic registration of protein structures based on their surface geometry

"TORINO 1911" project: A contribution of a SLAM-based survey to extensive 3D heritage modeling

In the framework of the digital documentation of complex environments the advanced Geomatics researches offers integrated solution and multi-sensor strategies for the 3D accurate reconstruction of stratified structures and articulated volumes in the heritage domain. The use of handheld devices for rapid mapping, both image- and range-based, can help the production of suitable easy-to use and easy-navigable 3D model for documentation projects. These types of reality-based modelling could support, with their tailored integrated geometric and radiometric aspects, valorisation and communication projects including virtual reconstructions, interactive navigation settings, immersive reality for dissemination purposes and evoking past places and atmospheres. The aim of this research is localized within the “Torino 1911” project, led by the University of San Diego (California) in cooperation with the PoliTo. The entire project is conceived for multi-scale reconstruction of the real and no longer existing structures in the whole park space of more than 400,000 m², for a virtual and immersive visualization of the Turin 1911 International “Fabulous Exposition” event, settled in the Valentino Park. Particularly, in the presented research, a 3D metric documentation workflow is proposed and validated in order to integrate the potentialities of LiDAR mapping by handheld SLAM-based device, the ZEB REVO Real Time instrument by GeoSLAM (2017 release), instead of TLS consolidated systems. Starting from these kind of models, the crucial aspects of the trajectories performances in the 3D reconstruction and the radiometric content from imaging approaches are considered, specifically by means of compared use of common DSLR cameras and portable sensors

Alpha, Betti and the Megaparsec Universe: on the Topology of the Cosmic Web

We study the topology of the Megaparsec Cosmic Web in terms of the scale-dependent Betti numbers, which formalize the topological information content of the cosmic mass distribution. While the Betti numbers do not fully quantify topology, they extend the information beyond conventional cosmological studies of topology in terms of genus and Euler characteristic. The richer information content of Betti numbers goes along the availability of fast algorithms to compute them. For continuous density fields, we determine the scale-dependence of Betti numbers by invoking the cosmologically familiar filtration of sublevel or superlevel sets defined by density thresholds. For the discrete galaxy distribution, however, the analysis is based on the alpha shapes of the particles. These simplicial complexes constitute an ordered sequence of nested subsets of the Delaunay tessellation, a filtration defined by the scale parameter, $\alpha$. As they are homotopy equivalent to the sublevel sets of the distance field, they are an excellent tool for assessing the topological structure of a discrete point distribution. In order to develop an intuitive understanding for the behavior of Betti numbers as a function of $\alpha$, and their relation to the morphological patterns in the Cosmic Web, we first study them within the context of simple heuristic Voronoi clustering models. Subsequently, we address the topology of structures emerging in the standard LCDM scenario and in cosmological scenarios with alternative dark energy content. The evolution and scale-dependence of the Betti numbers is shown to reflect the hierarchical evolution of the Cosmic Web and yields a promising measure of cosmological parameters. We also discuss the expected Betti numbers as a function of the density threshold for superlevel sets of a Gaussian random field.Comment: 42 pages, 14 figure