52 research outputs found

    Final Report: A Level-of-Detail Approach to Cluster-based Visualization

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    GPU-based volume visualization from high-order finite element fields

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    pre-printThis paper describes a new volume rendering system for spectral/hp finite-element methods that has as its goal to be both accurate and interactive. Even though high-order finite element methods are commonly used by scientists and engineers, there are few visualization methods designed to display this data directly. Consequently, visualizations of high-order data are generally created by first sampling the high-order field onto a regular grid and then generating the visualization via traditional methods based on linear interpolation. This approach, however, introduces error into the visualization pipeline and requires the user to balance image quality, interactivity, and resource consumption. We first show that evaluation of the volume rendering integral, when applied to the composition of piecewise-smooth transfer functions with the high-order scalar field, typically exhibits second-order convergence for a wide range of high-order quadrature schemes, and has worst case first-order convergence. This result provides bounds on the ability to achieve high-order convergence to the volume rendering integral. We then develop an algorithm for optimized evaluation of the volume rendering integral, based on the categorization of each ray according to the local behavior of the field and transfer function. We demonstrate the effectiveness of our system by running performance benchmarks on several high-order fluid-flow simulations

    Characterization of multiphase flows integrating X-ray imaging and virtual reality

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    Multiphase flows are used in a wide variety of industries, from energy production to pharmaceutical manufacturing. However, because of the complexity of the flows and difficulty measuring them, it is challenging to characterize the phenomena inside a multiphase flow. To help overcome this challenge, researchers have used numerous types of noninvasive measurement techniques to record the phenomena that occur inside the flow. One technique that has shown much success is X-ray imaging. While capable of high spatial resolutions, X-ray imaging generally has poor temporal resolution. This research improves the characterization of multiphase flows in three ways. First, an X-ray image intensifier is modified to use a high-speed camera to push the temporal limits of what is possible with current tube source X-ray imaging technology. Using this system, sample flows were imaged at 1000 frames per second without a reduction in spatial resolution. Next, the sensitivity of X-ray computed tomography (CT) measurements to changes in acquisition parameters is analyzed. While in theory CT measurements should be stable over a range of acquisition parameters, previous research has indicated otherwise. The analysis of this sensitivity shows that, while raw CT values are strongly affected by changes to acquisition parameters, if proper calibration techniques are used, acquisition parameters do not significantly influence the results for multiphase flow imaging. Finally, two algorithms are analyzed for their suitability to reconstruct an approximate tomographic slice from only two X-ray projections. These algorithms increase the spatial error in the measurement, as compared to traditional CT; however, they allow for very high temporal resolutions for 3D imaging. The only limit on the speed of this measurement technique is the image intensifier-camera setup, which was shown to be capable of imaging at a rate of at least 1000 FPS. While advances in measurement techniques for multiphase flows are one part of improving multiphase flow characterization, the challenge extends beyond measurement techniques. For improved measurement techniques to be useful, the data must be accessible to scientists in a way that maximizes the comprehension of the phenomena. To this end, this work also presents a system for using the Microsoft Kinect sensor to provide natural, non-contact interaction with multiphase flow data. Furthermore, this system is constructed so that it is trivial to add natural, non-contact interaction to immersive visualization applications. Therefore, multiple visualization applications can be built that are optimized to specific types of data, but all leverage the same natural interaction. Finally, the research is concluded by proposing a system that integrates the improved X-ray measurements, with the Kinect interaction system, and a CAVE automatic virtual environment (CAVE) to present scientists with the multiphase flow measurements in an intuitive and inherently three-dimensional manner

    Pinning down loosened prostheses : imaging and planning of percutaneous hip refixation

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    This thesis examines how computer software can be used to analyse medical images of an aseptically loosening hip prosthesis, and subsequently to plan and guide a minimally invasive cement injection procedure to stabilize the prosthesis. We addressed the detection and measurement of periprosthetic bone lesions from CT image volumes. Post-operative CTs of patients treated at our institution were analysed. We developed tissue classification algorithms that automatically label periprosthetic bone, cement and fibrous interface tissue. An existing particle-based multi-material meshing algorithm was adapted for improved Finite Element model creation. We then presented HipRFX, a proof-of-concept software tool for planning and guidance during percutaneous cement refixation procedures.Advanced School for Computing and Imaging (ASCI), Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO), Stichting Anna Fonds, Technologiestichting STWUBL - phd migration 201

    3D Multi-Scale Behavior of Granular Materials using Experimental and Numerical Techniques

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    Constitutive modeling of granular material behavior has generally been based on global response of laboratory-size specimens or larger models with little understanding of the fundamental mechanics that drive the global response. Many studies have acknowledged the importance of micro-scale and meso-scale mechanics on the constitutive behavior of granular materials. However, much knowledge is still missing to develop and improve robust micromechanical constitutive models. The research in this dissertation contributes to this knowledge gap for many potential applications using novel experimental techniques to investigate the three-dimensional (3D) behavior of granular materials. Critical micromechanics measurements at multiple scales are investigated by combining 3D synchrotron micro-computed tomography (SMT), 3D image analysis, and finite element analysis (FEA). At the single particle level (micro-scale), particle fracture was examined at strain rates of 0.2 mm/min and 2 m/s using quasi-static unconfined compression, unconfined mini-Kolsky bar, and x-ray imaging techniques. Surface reconstructions of particles were generated and exported to Abaqus FEA software, where quasi-static and higher rate loading curves and crack propagation were simulated with good accuracy. Stress concentrations in oddly shaped particles during FEA simulations resulted in more realistic fracture stresses than theoretical models. A nonlinear multivariable statistical model was developed to predict force required to fracture individual particles with known internal structure and loading geometry. At the meso-scale, 3D SMT imaging during in-situ triaxial testing of granular materials were used to identify particle morphology, contacts, kinematics and interparticle behavior. Micro shear bands (MSB) were exposed during pre-peak stress using a new relative particle displacement concept developed in this dissertation. MSB for spherical particles (glass beads) had larger thickness (3d50 to 5d50) than that of angular sands (such as F35 Ottawa sand, MSB thickness of 1d50 to 3d50). Particle morphology also plays a significant role in the onset and growth of shear bands and global fabric evolution of granular materials. More spherical particles typically exhibit more homogeneous internal anisotropy. Fabric of particles within the shear band (at higher densities and confining pressures) exhibits a peak and decrease into steady-state. Also, experimental fabric produces more accurate strength and deformation predictions in constitutive models that incorporate fabric evolution

    Doctor of Philosophy

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    dissertationHigh-order finite element methods, using either the continuous or discontinuous Galerkin formulation, are becoming more popular in fields such as fluid mechanics, solid mechanics and computational electromagnetics. While the use of these methods is becoming increasingly common, there has not been a corresponding increase in the availability and use of visualization methods and software that are capable of displaying visualizations of these volumes both accurately and interactively. A fundamental problem with the majority of existing visualization techniques is that they do not understand nor respect the structure of a high-order field, leading to visualization error. Visualizations of high-order fields are generally created by first approximating the field with low-order primitives and then generating the visualization using traditional methods based on linear interpolation. The approximation step introduces error into the visualization pipeline, which requires the user to balance the competing goals of image quality, interactivity and resource consumption. In practice, visualizations performed this way are often either undersampled, leading to visualization error, or oversampled, leading to unnecessary computational effort and resource consumption. Without an understanding of the sources of error, the simulation scientist is unable to determine if artifacts in the image are due to visualization error, insufficient mesh resolution, or a failure in the underlying simulation. This uncertainty makes it difficult for the scientists to make judgments based on the visualization, as judgments made on the assumption that artifacts are a result of visualization error when they are actually a more fundamental problem can lead to poor decision-making. This dissertation presents new visualization algorithms that use the high-order data in its native state, using the knowledge of the structure and mathematical properties of these fields to create accurate images interactively, while avoiding the error introduced by representing the fields with low-order approximations. First, a new algorithm for cut-surfaces is presented, specifically the accurate depiction of colormaps and contour lines on arbitrarily complex cut-surfaces. Second, a mathematical analysis of the evaluation of the volume rendering integral through a high-order field is presented, as well as an algorithm that uses this analysis to create accurate volume renderings. Finally, a new software system, the Element Visualizer (ElVis), is presented, which combines the ideas and algorithms created in this dissertation in a single software package that can be used by simulation scientists to create accurate visualizations. This system was developed and tested with the assistance of the ProjectX simulation team. The utility of our algorithms and visualization system are then demonstrated with examples from several high-order fluid flow simulations
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