Este trabalho apresenta o Animbs (Animation for MBS), um sistema capaz de visualizar dados gerados por um sistema de simulação de engenharia (SD/FAST) na forma de animações por computador. SD/FAST é um sistema utilizado para o modelamento e a simulação de sistemas mecânicos multicorpos (MBS). O sistema Animbs permite a associação de uma geometria ao MBS sendo simulado e utiliza os dados produzidos pela simulação do SD/FAST para criar uma animação do comportamento do sistema mecânico e, dessa forma, melhorar a análise de dados feita pelos usuários do SD/FAST. / This work presents Animbs (Animation for MBS), a software that enables the visualization of data generated by an engineering simulation system (SD/FAST) in the form of computer animation. SD/FAST is a system for modeling and simulation of multibody systems (MBS). The Animbs system allows the association of a geometry to the MBS being simulated, and uses the data produced by the SD/FAST simulation to create an animated view of the MBS behavior, thus providing support for enhanced data analysis by users of SD/FAST.

Humans are very effective at evaluating information visually. Scientific visualization is concerned with the process of presenting complex data in visual form to exploit this capability. A large array of tools is currently available for visual presentation. This research attempts to evaluate the effectiveness of three different presentation models that could be used for scientific visualization. The presentation models studied were, two-dimensional perspective rendering, field sequential stereoscopic three dimensional rendering and immersive virtual reality rendering. A large section of a three dimensional sub surface seismic survey was modeled as four-dimensional data by including a value for seismic reflectivity at each point in the survey. An artificial structure was randomly inserted into this data model and subjects were asked to locate and identify the structures. A group of seventeen volunteers from the University of Houston student body served as subjects for the study. Detection time, discrimination time and discrimination accuracy were recorded. The results showed large inter subject variation in presentation model preference. In addition the data suggest a possible gender effect. Female subjects had better overall performance on the task as well as better task acquisition.

Cyclones are complex weather phenomena, affected by multiple variables such as pressure, wind, temperature and more. Therefore, how cyclones are formed, what affects them and how they can be tracked is still actively researched today. Cyclones can have multiple centers (eyes), which can split and merge during its lifetime, which make them even more complex to define mathematically. In this thesis, how multi-center cyclones can be meaningfully visualized for domain scientists using multivariate visualization is investigated. An important aspect of the visualization is how a cyclone’s spread and boundary can be defined. The result is a visualization where the cyclonic region is defined by segmenting a pressure volume, and then a surface is extracted to get the cyclone’s boundary. Temperature is visualized using color mapping onto surfaces, while the wind velocity is shown using particles. The framework allows domain scientists to affect the visualization by picking criteria for segmenting the volume, color maps, and more. In conclusion, an improved cyclonic region could be defined by using multiple fields instead of only pressure, and the visualization would be improved with a greater detail put into the wind part. / <p>Examensarbetet är utfört vid Institutionen för teknik och naturvetenskap (ITN) vid Tekniska högskolan, Linköpings universitet</p>

This thesis describes the work of two students in collaboration with OpenSpace and the Community Coordinated Modelling Center (CCMC). The need expressed by both parties is a way to more accessibly visualize space weather data from the CCMC in OpenSpace. Firstly, space weather data is preprocessed for downloading and visualizing, a process that involves reducing the size of the data whilst keeping important features. Secondly, a pipeline is created for dynamically fetching the time varying data from the web during runtime of OpenSpace. A sliding window technique is employed to manage the downloading of the data. The results show a complete and working system for downloading data during runtime. Measurements of the performance of running the space weather visualizations by dynamically downloading versus running them locally, show that the new system impacts the frame time marginally. The results also show a visualization of space weather data with enhanced features, which facilitate the exploration of the data, and creates a more comprehensible representation of the data. Data is originally kept in a tabular FITS file format, and file sizes after data reduction and feature extractionare approximately 3% of the original file sizes.

Large-scale particle data sets, such as those computed in molecular dynamics (MD) simulations, are crucial to investigating important processes in physics and thermodynamics. The simulated atoms are usually visualized as hard spheres with Phong shading, where individual particles can be perceived well in close-up views. However, for large-scale simulations with millions of particles, the visualization of large fields-of-view usually suffers from strong aliasing artifacts, because the mismatch between data size and output resolution leads to severe under-sampling of the geometry. In this dissertation, we present novel visualization methods for large-scale particle data that address aliasing while enabling interactive high-quality rendering by sampling only the visible particles of a data set from a given view. The first contribution of this thesis is the novel concept of screen-space normal distribution functions (S-NDFs) for particle data. S-NDFs represent the distribution of surface normals that map to a given pixel in screen space, which enables high-quality re-lighting without re-rendering particles. In order to facilitate interactive zooming, we cache S-NDFs in a screen-space mipmap (S-MIP). Together, these two concepts enable interactive, scaleconsistent re-lighting and shading changes, as well as zooming, without having to re-sample the particle data. Our second contribution is a novel architecture for probabilistic culling of large particle data. Wedecouplethesuper-samplingforrenderingfromthedeterminationofsub-pixelparticle visibility, and perform culling probabilistically in multiple stages, while incrementally tracking confidence in the visibility data gathered so far to avoid wrong visibility decisions with high probability. Our architecture determines particle visibility with high accuracy, while only sampling a small part of the whole data set. The particles that are not occluded are then super-sampled for high rendering quality, at a fraction of the cost of sampling the entire data set.

Scientific visualization computer applications generate visual representations of large and complex sets of science data. These types of applications allow scientists to gain greater knowledge and insight into their data. For example, the visualization of environmental data is of particular interest to biologists when trying to understand how complex variables interact. Modern robotics and sensors have expanded the ability to collect environmental data, thus, the size and variety of these data-sets have likewise grown. Oftentimes, the collected data are deposited into files and databases where they sit in their separate and unique formats. Without easy to use visualization tools, it is difficult to understand and interpret the information within these data-sets. NORUS, the North America-Norway educational program, has a scientific focus on how climate-induced changes impact the living resources and ecosystems in the Arctic. In order to obtain the necessary science data, the NORUS program utilizes the Slocum Glider, a form of Autonomous Underwater Vehicle (AUV). This thesis aims to create a compelling, efficient, and easy to use interactive system for visualizing large sets of science data collected by the Slocum Glider. This goal is obtained through the implementation of various methods taken from scientific visualization, real time rendering, and scattered data interpolation. Methods include visualizations of the surrounding terrain, the ability to map various science data to glyphs, control over color mapping, scattered data interpolation and interactive camera control.

This project offers a multidisciplinary approach towards the acquisition, analysis and visualization of experimental data that pertain to cardiovascular applications. First and foremost, the capabilities of our Time-Resolved Digital Particle Image Velocimetry (TRDPIV) system were improved, allowing near-wall wall TRDPIV on compliant, dynamically moving boundaries. As a result, false flow-field vectors due to reflections from the boundary walls were eliminated, and allowing measurement of wall shear stress, wall shear rate, and oscillating shear index within as little as fifty microns of the boundary. Similar in-vitro measurements have not been reported to date by any other group. Second, an immersive, virtual environment (VE) was developed for the investigation and analysis of vortical, spatio-temporally developing flows with complex fluid-structure interactions. This VE was used to study flows in the cardiovascular system, particularly for flow through mechanical heart valves and inside the heart left ventricle (LV). The simulation provides three-dimensional (3-D) visualization of in-vitro heart flow mechanics, allowing global, volumetric flow analysis, and a useful environment for comparison with in-vivo MRI velocimetry data. 3-D glyphs (symbols representing informational parameters) are used to visually represent the flow parameters in the form of an ellipse attached to a cone, where the ellipse represents a second-order Reynolds stress tensor, and the cone represents the velocity magnitude and direction at a particular point in space, and the color corresponds to an out-of-plane vorticity. This new system has a major advantage over conventional 2-D systems in that it successfully doubles the number of visualized parameters, and allows for visualization of a time-dependent series of flow data in the Virginia Tech CAVETM immersive VE. The user controls his/her viewpoint, and can thus navigate through the simulation and view the flow field from any perspective in the immersive VE. Finally, an edge detection algorithm was developed to determine the inner and outer myocardial boundaries, and from this information calculate the local thickness distribution of the myocardium and a myocardial area approximation. This information is important in validating our in-vitro system, and is integral to the evaluation and diagnosis of congestive heart disease and its progression. / Master of Science

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