A feature extracting and meshing approach for sheet-like structures in rocks

Meshing rock samples with sheet-like structures based their CT scanned volumetric images, is a crucial component for both visualization and numerical simulation. In rocks, fractures and veins commonly exist in the form of sheet-like objects (e.g. thin layers and distinct flat shapes), which are much smaller than the rock mass dimensions. The representations of such objects require high-resolution 3D images with a huge dataset, which are difficult and even impossible to visualize or analyze by numerical methods. Therefore, we develop a microscopic image based meshing approach to extract major sheet-like structures and then preserve their major geometric features at the macroscale. This is achieved by the following four major steps: (1) extracting major objects through extending, separation and recovering operations based on the CT scanned data/microscopic images; (2) simplifying and constructing a simplified centroidal Voronoi diagram on the extracted structures; (3) generating triangular meshes to represent the structure; (4) generating volume tetrahedron meshes constrained with the above surface mesh as the internal surfaces. Moreover, a shape similarity approach is proposed to measure and evaluate how similar the generated mesh models to the original rock samples. It is applied as criteria for further mesh generation to better describe the rock features with fewer elements. Finally, a practical CT scanned rock is taken as an application example to demonstrate the usefulness and capability of the proposed approach

Effects of variable resistance on smart structures of cubic reconnaissance satellites in various thermal and frequency shocking conditions

Piezoelectric materials are widely used as smart structures in cubic reconnaissance satellites because of their sensing, actuating, and energy-harvesting abilities. In this study, an analytical model is developed in specific mechanical thermal shocking conditions. A special circuit and apparatus is designed for experimentation on the basis of the inverse piezoelectric effect. An equivalent circuit method is used to establish the relationship between the resistance and peak-to-peak voltage of lead zirconate titanate used as smart materials for cubic reconnaissance satellites. Various frequencies and resistance were applied in different mechanical thermal shocking conditions. Moreover, numerical simulations are conducted in various mechanical loading conditions to determine the accumulative effect. The model provides a novel mechanism to characterize the smart structures in cubic reconnaissance satellites. A rise in temperature increases peak-to-peak voltage; a rise in frequency decreases peak-to-peak voltage; and intensified resistance decreases peak-to-peak voltage. Based on experimentation and simulation, the optimum resistance is predicted for the various frequencies and temperatures. The various conditions may correspond to the different applications of smart structures for cubic reconnaissance satellites. The analytical calculations are in good agreement with experimental and numerical calculations. © 2017, The Korean Society of Mechanical Engineers and Springer-Verlag GmbH Germany

At-Most-Hexa Meshes

AbstractVolumetric polyhedral meshes are required in many applications, especially for solving partial differential equations on finite element simulations. Still, their construction bears several additional challenges compared to boundary‐based representations. Tetrahedral meshes and (pure) hex‐meshes are two popular formats in scenarios like CAD applications, offering opposite advantages and disadvantages. Hex‐meshes are more intricate to construct due to the global structure of the meshing, but feature much better regularity, alignment, are more expressive, and offer the same simulation accuracy with fewer elements. Hex‐dominant meshes, where most but not all cell elements have a hexahedral structure, constitute an attractive compromise, potentially unlocking benefits from both structures, but their generality makes their employment in downstream applications difficult. In this work, we introduce a strict subset of general hex‐dominant meshes, which we term 'at‐most‐hexa meshes', in which most cells are still hexahedral, but no cell has more than six boundary faces, and no face has more than four sides. We exemplify the ease of construction of at‐most‐hexa meshes by proposing a frugal and straightforward method to generate high‐quality meshes of this kind, starting directly from hulls or point clouds, for example, from a 3D scan. In contrast to existing methods for (pure) hexahedral meshing, ours does not require an intermediate parameterization of other costly pre‐computations and can start directly from surfaces or samples. We leverage a Lloyd relaxation process to exploit the synergistic effects of aligning an orientation field in a modified 3D Voronoi diagram using the norm for cubical cells. The extracted geometry incorporates regularity as well as feature alignment, following sharp edges and curved boundary surfaces. We introduce specialized operations on the three‐dimensional graph structure to enforce consistency during the relaxation. The resulting algorithm allows for an efficient evaluation with parallel algorithms on GPU hardware and completes even large reconstructions within minutes

Unstructured and semi-structured hexahedral mesh generation methods

Discretization techniques such as the finite element method, the finite volume method or the discontinuous Galerkin method are the most used simulation techniques in ap- plied sciences and technology. These methods rely on a spatial discretization adapted to the geometry and to the prescribed distribution of element size. Several fast and robust algorithms have been developed to generate triangular and tetrahedral meshes. In these methods local connectivity modifications are a crucial step. Nevertheless, in hexahedral meshes the connectivity modifications propagate through the mesh. In this sense, hexahedral meshes are more constrained and therefore, more difficult to gener- ate. However, in many applications such as boundary layers in computational fluid dy- namics or composite material in structural analysis hexahedral meshes are preferred. In this work we present a survey of developed methods for generating structured and unstructured hexahedral meshes.Peer ReviewedPostprint (published version

Doctor of Philosophy

dissertationVolumetric parameterization is an emerging field in computer graphics, where volumetric representations that have a semi-regular tensor-product structure are desired in applications such as three-dimensional (3D) texture mapping and physically-based simulation. At the same time, volumetric parameterization is also needed in the Isogeometric Analysis (IA) paradigm, which uses the same parametric space for representing geometry, simulation attributes and solutions. One of the main advantages of the IA framework is that the user gets feedback directly as attributes of the NURBS model representation, which can represent geometry exactly, avoiding both the need to generate a finite element mesh and the need to reverse engineer the simulation results from the finite element mesh back into the model. Research in this area has largely been concerned with issues of the quality of the analysis and simulation results assuming the existence of a high quality volumetric NURBS model that is appropriate for simulation. However, there are currently no generally applicable approaches to generating such a model or visualizing the higher order smooth isosurfaces of the simulation attributes, either as a part of current Computer Aided Design or Reverse Engineering systems and methodologies. Furthermore, even though the mesh generation pipeline is circumvented in the concept of IA, the quality of the model still significantly influences the analysis result. This work presents a pipeline to create, analyze and visualize NURBS geometries. Based on the concept of analysis-aware modeling, this work focusses in particular on methodologies to decompose a volumetric domain into simpler pieces based on appropriate midstructures by respecting other relevant interior material attributes. The domain is decomposed such that a tensor-product style parameterization can be established on the subvolumes, where the parameterization matches along subvolume boundaries. The volumetric parameterization is optimized using gradient-based nonlinear optimization algorithms and datafitting methods are introduced to fit trivariate B-splines to the parameterized subvolumes with guaranteed order of accuracy. Then, a visualization method is proposed allowing to directly inspect isosurfaces of attributes, such as the results of analysis, embedded in the NURBS geometry. Finally, the various methodologies proposed in this work are demonstrated on complex representations arising in practice and research