Use of Graded Laser Scanning to Generate Efficient Boundary Element Meshes

This thesis presents an approach which combines a reverse engineering technique with boundary element stress analysis, by generating a graded mesh to improve the simulation efficiency. A rectangular metal plate, a bar of a circular cross section, a gas turbine blade and a steam turbine blade were scanned at different resolutions using a (non-contact) laser scanner measurement to obtain the point clouds. Meshes of each object were generated in Rapidform and directly used in a boundary element stress analysis. In addition, the steam turbine blade was scanned using different scanning resolutions. From this, a graded mesh model of the blade was generated and then efficient boundary element stress analyses were performed. An application of a freeform surface reconstruction of a blade surface is also given. Also, several Matlab programs were written to repair the edges and the cylindrical surface of the meshes

An investigation on the framework of dressing virtual humans

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Realistic human models are widely used in variety of applications. Much research has been carried out on improving realism of virtual humans from various aspects, such as body shapes, hair, and facial expressions and so on. In most occasions, these virtual humans need to wear garments. However, it is time-consuming and tedious to dress a human model using current software packages [Maya2004]. Several methods for dressing virtual humans have been proposed recently [Bourguignon2001, Turquin2004, Turquin2007 and Wang2003B]. The method proposed by Bourguignon et al [Bourguignon2001] can only generate 3D garment contour instead of 3D surface. The method presented by Turquin et al. [Turquin2004, Turquin2007] could generate various kinds of garments from sketches but their garments followed the shape of the body and the side of a garment looked not convincing because of using simple linear interpolation. The method proposed by Wang et al. [Wang2003B] lacked interactivity from users, so users had very limited control on the garment shape.This thesis proposes a framework for dressing virtual humans to obtain convincing dressing results, which overcomes problems existing in previous papers mentioned above by using nonlinear interpolation, level set-based shape modification, feature constraints and so on. Human models used in this thesis are reconstructed from real human body data obtained using a body scanning system. Semantic information is then extracted from human models to assist in generation of 3 dimensional (3D) garments. The proposed framework allows users to dress virtual humans using garment patterns and sketches. The proposed dressing method is based on semantic virtual humans. A semantic human model is a human body with semantic information represented by certain of structure and body features. The semantic human body is reconstructed from body scanned data from a real human body. After segmenting the human model into six parts some key features are extracted. These key features are used as constraints for garment construction.Simple 3D garment patterns are generated using the techniques of sweep and offset. To dress a virtual human, users just choose a garment pattern, which is put on the human body at the default position with a default size automatically. Users are allowed to change simple parameters to specify some sizes of a garment by sketching the desired position on the human body.To enable users to dress virtual humans by their own design styles in an intuitive way, this thesis proposes an approach for garment generation from user-drawn sketches. Users can directly draw sketches around reconstructed human bodies and then generates 3D garments based on user-drawn strokes. Some techniques for generating 3D garments and dressing virtual humans are proposed. The specific focus of the research lies in generation of 3D geometric garments, garment shape modification, local shape modification, garment surface processing and decoration creation. A sketch-based interface has been developed allowing users to draw garment contour representing the front-view shape of a garment, and the system can generate a 3D geometric garment surface accordingly. To improve realism of a garment surface, this thesis presents three methods as follows. Firstly, the procedure of garment vertices generation takes key body features as constraints. Secondly, an optimisation algorithm is carried out after generation of garment vertices to optimise positions of garment vertices. Finally, some mesh processing schemes are applied to further process the garment surface. Then, an elaborate 3D geometric garment surface can be obtained through this series of processing. Finally, this thesis proposes some modification and editing methods. The user-drawn sketches are processed into spline curves, which allow users to modify the existing garment shape by dragging the control points into desired positions. This makes it easy for users to obtain a more satisfactory garment shape compared with the existing one. Three decoration tools including a 3D pen, a brush and an embroidery tool, are provided letting users decorate the garment surface by adding some small 3D details such as brand names, symbols and so on. The prototype of the framework is developed using Microsoft Visual Studio C++,OpenGL and GPU programming

Recognition of Planar Segments in Point Cloud Based on Wavelet Transform

Within industrial automation systems, three-dimensional (3-D) vision provides very useful feedback information in autonomous operation of various manufacturing equipment (e.g., industrial robots, material handling devices, assembly systems, and machine tools). The hardware performance in contemporary 3-D scanning devices is suitable for online utilization. However, the bottleneck is the lack of real-time algorithms for recognition of geometric primitives (e.g., planes and natural quadrics) from a scanned point cloud. One of the most important and the most frequent geometric primitive in various engineering tasks is plane. In this paper, we propose a new fast one-pass algorithm for recognition (segmentation and fitting) of planar segments from a point cloud. To effectively segment planar regions, we exploit the orthonormality of certain wavelets to polynomial function, as well as their sensitivity to abrupt changes. After segmentation of planar regions, we estimate the parameters of corresponding planes using standard fitting procedures. For point cloud structuring, a z-buffer algorithm with mesh triangles representation in barycentric coordinates is employed. The proposed recognition method is tested and experimentally validated in several real-world case studies

Method to Automatically Register Scattered Point Clouds Based on Principal Pose Estimation

Three dimensional (3-D) modeling is important in applications ranging from manufacturing to entertainment. Multiview registration is one of the crucial steps in 3-D model construction. The automatic establishment of correspondences between overlapping views, without any known initial information, is the main challenge in point clouds registration. An automatic registration algorithm is proposed to solve the registration problem of rigid, unordered, scattered point clouds. This approach is especially suitable for registering datasets that are lacking in features or texture. In general, the existing techniques exhibit significant limitations in the registration of these types of point cloud data. The presented method automatically determines the best coarse registration results by exploiting the statistical technique principal component analysis and outputs translation matrices as the initial estimation for fine registration. Then, the translation matrices obtained from coarse registration algorithms are used to update the original point cloud and the optimal translation matrices are solved using an iterative algorithm. Experimental results show that the proposed algorithm is time efficient and accurate, even if the point clouds are partially overlapped and containing large missing regions

Re-design of drivers’ car seat using three dimensional reverse engineering

Automobile seat design in current practice requires satisfying the ergonomics guidelines as well as considers the comfort expectation of the population. The main aim is to re-examine the existing car seat designs and to propose a novel seat design for better comfort. The number of cars reviewed for drivers’ seat features and user comfort are based on the analysis using a statistical tool. The statistical tool analysis is defined using data from the survey conducted. The proposed design is obtained using the 3-D Reverse Engineering procedure on the selected car seat models. The result is assessed to show that the modified car seat design is superior in terms of form, shape, seat features, usability and comfort. Through this work, the basic seat needs while driving, for example pain preclusion aspects and comfort weightage are defined. The survey done can expunge the expenditure for test experimentations in the future and the proposed methodology can be useful in establishing new design standards for the seat

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

Integrated tactile-optical coordinate measurement for the reverse engineering of complex geometry

Complex design specifications and tighter tolerances are increasingly required in modern engineering applications, either for functional or aesthetic demands. Multiple sensors are therefore exploited to achieve both holistic measurement information and improved reliability or reduced uncertainty of measurement data. Multi-sensor integration systems can combine data from several information sources (sensors) into a common representational format in order that the measurement evaluation can benefit from all available sensor information and data. This means a multi-sensor system is able to provide more efficient solutions and better performances than a single sensor based system. This thesis develops a compensation approach for reverse engineering applications based on the hybrid tactile-optical multi-sensor system. In the multi-sensor integration system, each individual sensor should be configured to its optimum for satisfactory measurement results. All the data measured from different equipment have to be precisely integrated into a common coordinate system. To solve this problem, this thesis proposes an accurate and flexible method to unify the coordinates of optical and tactile sensors for reverse engineering. A sphere-plate artefact with nine spheres is created and a set of routines are developed for data integration of a multi-sensor system. Experimental results prove that this novel centroid approach is more accurate than the traditional method. Thus, data sampled by different measuring devices, irrespective of their location can be accurately unified. This thesis describes a competitive integration for reverse engineering applications where the point cloud data scanned by the fast optical sensor is compensated and corrected by the slower, but more accurate tactile probe measurement to improve its overall accuracy. A new competitive approach for rapid and accurate reverse engineering of geometric features from multi-sensor systems based on a geometric algebra approach is proposed and a set of programs based on the MATLAB platform has been generated for the verification of the proposed method. After data fusion, the measurement efficiency is improved 90% in comparison to the tactile method and the accuracy of the reconstructed geometric model is improved from 45 micrometres to 7 micrometres in comparison to the optical method, which are validated by case study

Generation and detection of defects in metallic parts fabricated by selective laser melting and electron beam melting and their effects on mechanical properties.

Application of Additive Manufacturing (AM) technology to fabricate complex three-dimensional components is one promising direction within the manufacturing industry. This approach is rapidly changing the way designers and engineers create objects with desired shape and structures. Selective Laser Melting (SLM) and Electron Beam Melting (EBM) are two common powder bed fusion processes within AM for fabricating metallic parts. In order to give designers and engineers more insights into employing AM, the quality and long-term behavior of SLM- and EBM-produced parts need to be carefully investigated. Thus, this research project aims to understand how processing parameters affect defect generation and distribution during SLM and EBM processes, to study the morphological features of defects, to identify effective non-destructive method(s) to detect these defects, and to characterize the effect of defects on mechanical properties of SLM- and EBM-produced parts. The study began by generating stochastic defects via adjustment to process parameters from optimal parameters to marginal parameters, in order to correlate the porosity to the marginal parameters. Archimedes method was employed to estimate porosity of SLM- and EBM-produced specimens. After this, by using destructive characterization techniques, the defective specimens were sectioned. The morphology of stochastic defects was investigated based on their contour features on the cross sections. Micro CT was primarily used to evaluate the stochastic defects in the SLM and EBM parts and demonstrate their morphological characteristics and porosity in the single slices and reconstructed models. Finally, tensile and fatigue tests were carried out on Ti-6Al-4V parts with identified porosity. The fracture mechanism was analyzed. This study established a fundamental understanding of defects in parts made by SLM and EBM processes. Porosity was quantitatively correlated to the marginal parameters of SLM and EBM processes. Defects were differentiated based on their morphological properties and features. Micro CT was confirmed to be an effective non-destructive method for evaluating stochastic defects in SLM- and EBM-produced parts. The effects of stochastic defects on Ti-6Al-4V parts were determined based on tensile and fatigue tests. It was found that both microstructure and porosity have an impact on the mechanical properties of SLM- and EBM-produced parts