Computational Design of Cold Bent Glass Fa\c{c}ades

Cold bent glass is a promising and cost-efficient method for realizing doubly curved glass fa\c{c}ades. They are produced by attaching planar glass sheets to curved frames and require keeping the occurring stress within safe limits. However, it is very challenging to navigate the design space of cold bent glass panels due to the fragility of the material, which impedes the form-finding for practically feasible and aesthetically pleasing cold bent glass fa\c{c}ades. We propose an interactive, data-driven approach for designing cold bent glass fa\c{c}ades that can be seamlessly integrated into a typical architectural design pipeline. Our method allows non-expert users to interactively edit a parametric surface while providing real-time feedback on the deformed shape and maximum stress of cold bent glass panels. Designs are automatically refined to minimize several fairness criteria while maximal stresses are kept within glass limits. We achieve interactive frame rates by using a differentiable Mixture Density Network trained from more than a million simulations. Given a curved boundary, our regression model is capable of handling multistable configurations and accurately predicting the equilibrium shape of the panel and its corresponding maximal stress. We show predictions are highly accurate and validate our results with a physical realization of a cold bent glass surface

Sketching space

In this paper, we present a sketch modelling system which we call Stilton. The program resembles a desktop VRML browser, allowing a user to navigate a three-dimensional model in a perspective projection, or panoramic photographs, which the program maps onto the scene as a `floor' and `walls'. We place an imaginary two-dimensional drawing plane in front of the user, and any geometric information that user sketches onto this plane may be reconstructed to form solid objects through an optimization process. We show how the system can be used to reconstruct geometry from panoramic images, or to add new objects to an existing model. While panoramic imaging can greatly assist with some aspects of site familiarization and qualitative assessment of a site, without the addition of some foreground geometry they offer only limited utility in a design context. Therefore, we suggest that the system may be of use in `just-in-time' CAD recovery of complex environments, such as shop floors, or construction sites, by recovering objects through sketched overlays, where other methods such as automatic line-retrieval may be impossible. The result of using the system in this manner is the `sketching of space' - sketching out a volume around the user - and once the geometry has been recovered, the designer is free to quickly sketch design ideas into the newly constructed context, or analyze the space around them. Although end-user trials have not, as yet, been undertaken we believe that this implementation may afford a user-interface that is both accessible and robust, and that the rapid growth of pen-computing devices will further stimulate activity in this area

IST Austria Thesis

Fabrication of curved shells plays an important role in modern design, industry, and science. Among their remarkable properties are, for example, aesthetics of organic shapes, ability to evenly distribute loads, or efficient flow separation. They find applications across vast length scales ranging from sky-scraper architecture to microscopic devices. But, at the same time, the design of curved shells and their manufacturing process pose a variety of challenges. In this thesis, they are addressed from several perspectives. In particular, this thesis presents approaches based on the transformation of initially flat sheets into the target curved surfaces. This involves problems of interactive design of shells with nontrivial mechanical constraints, inverse design of complex structural materials, and data-driven modeling of delicate and time-dependent physical properties. At the same time, two newly-developed self-morphing mechanisms targeting flat-to-curved transformation are presented. In architecture, doubly curved surfaces can be realized as cold bent glass panelizations. Originally flat glass panels are bent into frames and remain stressed. This is a cost-efficient fabrication approach compared to hot bending, when glass panels are shaped plastically. However such constructions are prone to breaking during bending, and it is highly nontrivial to navigate the design space, keeping the panels fabricable and aesthetically pleasing at the same time. We introduce an interactive design system for cold bent glass façades, while previously even offline optimization for such scenarios has not been sufficiently developed. Our method is based on a deep learning approach providing quick and high precision estimation of glass panel shape and stress while handling the shape multimodality. Fabrication of smaller objects of scales below 1 m, can also greatly benefit from shaping originally flat sheets. In this respect, we designed new self-morphing shell mechanisms transforming from an initial flat state to a doubly curved state with high precision and detail. Our so-called CurveUps demonstrate the encodement of the geometric information into the shell. Furthermore, we explored the frontiers of programmable materials and showed how temporal information can additionally be encoded into a flat shell. This allows prescribing deformation sequences for doubly curved surfaces and, thus, facilitates self-collision avoidance enabling complex shapes and functionalities otherwise impossible. Both of these methods include inverse design tools keeping the user in the design loop

Eta Carinae in the Context of the Most Massive Stars

Eta Car, with its historical outbursts, visible ejecta and massive, variable winds, continues to challenge both observers and modelers. In just the past five years over 100 papers have been published on this fascinating object. We now know it to be a massive binary system with a 5.54-year period. In January 2009, Eta Car underwent one of its periodic low-states, associated with periastron passage of the two massive stars. This event was monitored by an intensive multi-wavelength campaign ranging from gamma-rays to radio. A large amount of data was collected to test a number of evolving models including 3-D models of the massive interacting winds. August 2009 was an excellent time for observers and theorists to come together and review the accumulated studies, as have occurred in four meetings since 1998 devoted to Eta Car. Indeed, Eta Car behaved both predictably and unpredictably during this most recent periastron, spurring timely discussions. Coincidently, WR140 also passed through periastron in early 2009. It, too, is a intensively studied massive interacting binary. Comparison of its properties, as well as the properties of other massive stars, with those of Eta Car is very instructive. These well-known examples of evolved massive binary systems provide many clues as to the fate of the most massive stars. What are the effects of the interacting winds, of individual stellar rotation, and of the circumstellar material on what we see as hypernovae/supernovae? We hope to learn.Comment: 26 pages, 7 figures, IAU General Assembly Joint Discussion on Eta Carinae in Context of the Most Massive Star

Specifying a hybrid, multiple material CAD system for next-generation prosthetic design

For many years, the biggest issue that causes discomfort and hygiene issues for patients with lower limb amputations have been the interface between body and prosthetic, the socket. Often made of an inflexible, solid polymer that does not allow the residual limb to breathe or perspire and with no consideration for the changes in size and shape of the human body caused by changes in temperature or environment, inflammation, irritation and discomfort often cause reduced usage or outright rejection of the prosthetic by the patient in their day to day lives. To address these issues and move towards a future of improved quality of life for patients who suffer amputations, Loughborough University formed the Next Generation Prosthetics research cluster. This work is one of four multidisciplinary research studies conducted by members of this research cluster, focusing on the area of Computer Aided Design (CAD) for improving the interface with Additive Manufacture (AM) to solve some of the challenges presented with improving prosthetic socket design, with an aim to improve and streamline the process to enable the involvement of clinicians and patients in the design process. The research presented in this thesis is based on three primary studies. The first study involved the conception of a CAD criteria, deciding what features are needed to represent the various properties the future socket outlined by the research cluster needs. These criteria were then used for testing three CAD systems, one each from the Parametric, Non Uniform Rational Basis Spline (NURBS) and Polygon archetypes respectively. The result of these tests led to the creation of a hybrid control workflow, used as the basis for finding improvements. The second study explored emerging CAD solutions, various new systems or plug-ins that had opportunities to improve the control model. These solutions were tested individually in areas where they could improve the workflow, and the successful solutions were added to the hybrid workflow to improve and reduce the workflow further. The final study involved taking the knowledge gained from the literature and the first two studies in order to theorise how an ideal CAD system for producing future prosthetic sockets would work, with considerations for user interface issues as well as background CAD applications. The third study was then used to inform the final deliverable of this research, a software design specification that defines how the system would work. This specification was written as a challenge to the CAD community, hoping to inform and aid future advancements in CAD software. As a final stage of research validation, a number of members of the CAD community were contacted and interviewed about their feelings of the work produced and their feedback was taken in order to inform future research in this area

Automated visual inspection for the quality control of pad printing

Pad printing is used to decorate consumer goods largely because of its unique ability to apply graphics to doubly curved surfaces. The Intelpadrint project was conceived to develop a better understanding of the process and new printing pads, inks and printers. The thesis deals primarily with the research of a printer control system including machine vision. At present printing is manually controlled. Operator knowledge was gathered for use by an expert system to control the process. A novel local corner- matching algorithm was conceived to effect image segmentation, and neuro-fuzzy techniques were used to recognise patterns in printing errors. Non-linear Finite Element Analysis of the rubber printing-pad led to a method for pre-distorting artwork so that it would print undistorted on a curved product. A flexible, more automated printer was developed that achieves a higher printing rate. Ultraviolet-cured inks with improved printability were developed. The image normalisation/ error-signalling stage in inspection was proven in isolation, as was the pattern recognition system

Feature-sensitive and Adaptive Image Triangulation: A Super-pixel-based Scheme for Image Segmentation and Mesh Generation

With increasing utilization of various imaging techniques (such as CT, MRI and PET) in medical fields, it is often in great need to computationally extract the boundaries of objects of interest, a process commonly known as image segmentation. While numerous approaches have been proposed in literature on automatic/semi-automatic image segmentation, most of these approaches are based on image pixels. The number of pixels in an image can be huge, especially for 3D imaging volumes, which renders the pixel-based image segmentation process inevitably slow. On the other hand, 3D mesh generation from imaging data has become important not only for visualization and quantification but more critically for finite element based numerical simulation. Traditionally image-based mesh generation follows such a procedure as: (1) image boundary segmentation, (2) surface mesh generation from segmented boundaries, and (3) volumetric (e.g., tetrahedral) mesh generation from surface meshes. These three majors steps have been commonly treated as separate algorithms/steps and hence image information, once segmented, is not considered any more in mesh generation. In this thesis, we investigate a super-pixel based scheme that integrates both image segmentation and mesh generation into a single method, making mesh generation truly an image-incorporated approach. Our method, called image content-aware mesh generation, consists of several main steps. First, we generate a set of feature-sensitive, and adaptively distributed points from 2D grayscale images or 3D volumes. A novel image edge enhancement method via randomized shortest paths is introduced to be an optional choice to generate the features’ boundary map in mesh node generation step. Second, a Delaunay-triangulation generator (2D) or tetrahedral mesh generator (3D) is then utilized to generate a 2D triangulation or 3D tetrahedral mesh. The generated triangulation (or tetrahedralization) provides an adaptive partitioning of a given image (or volume). Each cluster of pixels within a triangle (or voxels within a tetrahedron) is called a super-pixel, which forms one of the nodes of a graph and adjacent super-pixels give an edge of the graph. A graph-cut method is then applied to the graph to define the boundary between two subsets of the graph, resulting in good boundary segmentations with high quality meshes. Thanks to the significantly reduced number of elements (super-pixels) as compared to that of pixels in an image, the super-pixel based segmentation method has tremendously improved the segmentation speed, making it feasible for real-time feature detection. In addition, the incorporation of image segmentation into mesh generation makes the generated mesh well adapted to image features, a desired property known as feature-preserving mesh generation

Vision Sensors and Edge Detection

Vision Sensors and Edge Detection book reflects a selection of recent developments within the area of vision sensors and edge detection. There are two sections in this book. The first section presents vision sensors with applications to panoramic vision sensors, wireless vision sensors, and automated vision sensor inspection, and the second one shows image processing techniques, such as, image measurements, image transformations, filtering, and parallel computing