Hybrid modelling of heterogeneous volumetric objects.

Heterogeneous multi-material volumetric modelling is an emerging and rapidly developing field. A Heterogeneous object is a volumetric object with interior structure where different physically-based attributes are defined. The attributes can be of different nature: material distributions, density, microstructures, optical properties and others. Heterogeneous objects are widely used where the presence of the interior structures is an important part of the model. Computer-aided design (CAD), additive manufacturing, physical simulations, visual effects, medical visualisation and computer art are examples of such applications. In particular, digital fabrication employing multi-material 3D printing techniques is becoming omnipresent. However, the specific methods and tools for representation, modelling, rendering, animation and fabrication of multi-material volumetric objects with attributes are only starting to emerge. The need for adequate unifying theoretical and practical framework has been obvious. Developing adequate representational schemes for heterogeneous objects is in the core of research in this area. The most widely used representations for defining heterogeneous objects are boundary representation, distance-based representations, function representation and voxels. These representations work well for modelling homogeneous (solid) objects but they all have significant drawbacks when dealing with heterogeneous objects. In particular, boundary representation, while maintaining its prevailing role in computer graphics and geometric modelling, is not inherently natural for dealing with heterogeneous objects especially in the con- text of additive manufacturing and 3D printing, where multi-material properties are paramount as well as in physical simulation where the exact representation rather than an approximate one can be important. In this thesis, we introduce and systematically describe a theoretical and practical framework for modelling volumetric heterogeneous objects on the basis of a novel unifying functionally-based hybrid representation called HFRep. It is based on the function representation (FRep) and several distance-based representations, namely signed distance fields (SDFs), adaptively sampled distance fields (ADFs) and interior distance fields (IDFs). It embraces advantages and circumvents disadvantages of the initial representations. A mathematically substantiated theoretical description of the HFRep with an emphasis on defining functions for HFRep objects’ geometry and attributes is provided. This mathematical framework serves as the basis for developing efficient algorithms for the generation of HFRep objects taking into account both their geometry and attributes. To make the proposed approach practical, a detailed description of efficient algorithmic procedures has been developed. This has required employing a number of novel techniques of different nature, separately and in combination. In particular, an extension of a fast iterative method (FIM) for numerical solving of the eikonal equation on hierarchical grids was developed. This allowed for efficient computation of smooth distance-based attributes. To prove the concept, the main elements of the framework have been implemented and used in several applications of different nature. It was experimentally shown that the developed methods and tools can be used for generating objects with complex interior structure, e.g. microstructures, and different attributes. A special consideration has been devoted to applications of dynamic nature. A novel concept of heterogeneous space-time blending (HSTB) method with an automatic control for metamorphosis of heterogeneous objects with textures, both in 2D and 3D, has been introduced, algorithmised and implemented. We have applied the HSTB in the context of ‘4D Cubism’ project. There are plans to use the developed methods and tools for many other applications

Hybrid Function Representation for Heterogeneous Objects

Heterogeneous object modelling is an emerging area where geometric shapes are considered in concert with their internal physically-based attributes. This paper describes a novel theoretical and practical framework for modelling volumetric heterogeneous objects on the basis of a novel unifying functionally-based hybrid representation called HFRep. This new representation allows for obtaining a continuous smooth distance field in Euclidean space and preserves the advantages of the conventional representations based on scalar fields of different kinds without their drawbacks. We systematically describe the mathematical and algorithmic basics of HFRep. The steps of the basic algorithm are presented in detail for both geometry and attributes. To solve some problematic issues, we have suggested several practical solutions, including a new algorithm for solving the eikonal equation on hierarchical grids. Finally, we show the practicality of the approach by modelling several representative heterogeneous objects, including those of a time-variant nature

Adequate Inner Bound for Geometric Modeling with Compact Field Function

International audienceRecent advances in implicit surface modeling now provide highly controllable blending effects. These effects rely on the field functions of $\mathbb{R}^3 \rightarrow \mathbb{R}$ in which the implicit surfaces are defined. In these fields, there is an outside part in which blending is defined and an inside part. The implicit surface is the interface between these two parts. As recent operators often focus on blending, most efforts have been made on the outer part of field functions and little attention has been paid on the inner part. Yet, the inner fields are important as soon as difference and intersection operators are used. This makes its quality as crucial as the quality of the outside. In this paper, we analyze these shortcomings, and deduce new constraints on field functions such that differences and intersections can be seamlessly applied without introducing discontinuities or field distortions. In particular, we show how to adapt state of the art gradient-based union and blending operators to our new constraints. Our approach enables a precise control of the shape of both the inner or outer field boundaries. We also introduce a new set of asymmetric operators tailored for the modeling of fine details while preserving the integrity of the resulting fields

Adapted Delaunay triangulation method for free-form surface generation from random point clouds for stochastic optimization applications

Free-form surfaces are defined with NURBS (non-uniform rational basis spline) for most computer-aided engineering (CAE) applications. The NURBS method requires the definition of parameters such as weights, knot vectors and degree of the curves which make the configuration of the surface computationally expensive and complex. When the control points are randomly spaced in the point cloud and the topology of the desired surface is unknown, surface configuration with NURBS method becomes a challenging task. Optimization attempts for such surfaces create enormous amounts of computing data when coupled with physics solvers such as finite element analysis (FEA) tools and computational fluid dynamics (CFD) tools. In this paper, an adapted Delaunay triangulation (ADT) method for surface generation from the random points cloud is proposed and compared with widely used implicit functions based NURBS fitting method. The surface generated from ADT method can be simultaneously used with stochastic optimization algorithms (SOA) and CFD applications to search for the optimal results with minimum computational costs. It was observed while comparing ADT with NURBS-based geometry configuration that the computation time can be reduced by 3 folds. The corresponding deviation between both geometry configuration methods has been observed as low as 5% for all optimisation scenarios during the comparison. In addition, ADT method can provide light weight CFD approach as any instance of design iteration has at least half storage footprint as compared to corresponding NURBS surface. The proposed approach provides novel methodology towards establishing light weight CFD geometry, absence of which currently isolates methodologies for optimization and CFD analysis

Recent Developments in the Numerics of Nonlinear Hyperbolic Conservation Laws

The development of reliable numerical methods for the simulation of real life problems requires both a fundamental knowledge in the field of numerical analysis and a proper experience in practical applications as well as their mathematical modeling. Thus, the purpose of the workshop was to bring together experts not only from the field of applied mathematics but also from civil and mechanical engineering working in the area of modern high order methods for the solution of partial differential equations or even approximation theory necessary to improve the accuracy as well as robustness of numerical algorithms

New Models for High-Quality Surface Reconstruction and Rendering

The efficient reconstruction and artifact-free visualization of surfaces from measured real-world data is an important issue in various applications, such as medical and scientific visualization, quality control, and the media-related industry. The main contribution of this thesis is the development of the first efficient GPU-based reconstruction and visualization methods using trivariate splines, i.e., splines defined on tetrahedral partitions. Our methods show that these models are very well-suited for real-time reconstruction and high-quality visualizations of surfaces from volume data. We create a new quasi-interpolating operator which for the first time solves the problem of finding a globally C1-smooth quadratic spline approximating data and where no tetrahedra need to be further subdivided. In addition, we devise a new projection method for point sets arising from a sufficiently dense sampling of objects. Compared with existing approaches, high-quality surface triangulations can be generated with guaranteed numerical stability. Keywords. Piecewise polynomials; trivariate splines; quasi-interpolation; volume data; GPU ray casting; surface reconstruction; point set surface

New Models for High-Quality Surface Reconstruction and Rendering

The efficient reconstruction and artifact-free visualization of surfaces from measured real-world data is an important issue in various applications, such as medical and scientific visualization, quality control, and the media-related industry. The main contribution of this thesis is the development of the first efficient GPU-based reconstruction and visualization methods using trivariate splines, i.e., splines defined on tetrahedral partitions. Our methods show that these models are very well-suited for real-time reconstruction and high-quality visualizations of surfaces from volume data. We create a new quasi-interpolating operator which for the first time solves the problem of finding a globally C1-smooth quadratic spline approximating data and where no tetrahedra need to be further subdivided. In addition, we devise a new projection method for point sets arising from a sufficiently dense sampling of objects. Compared with existing approaches, high-quality surface triangulations can be generated with guaranteed numerical stability. Keywords. Piecewise polynomials; trivariate splines; quasi-interpolation; volume data; GPU ray casting; surface reconstruction; point set surface