Local Exact Particle Tracing on Unstructured Grids

For analyzing and interpreting results of flow simulations, particle tracing is a well established visualization method. In addition, it is a preliminary step for more advanced techniques such as line integral convolution. For interactive exploration of large data sets, a very efficient and reliable particle tracing method is needed. For wind channel experiments or flight simulations, large unstructured computational grids have become common practice. Traditional approachs, based on numerical integration methods of ordinary differential equations however fail to deliver sufficiently accurate path calculation at the speed required for interactive use. In this paper we extend the local exact approach of Nielson and Jung in such a way that it can be used for interactive particle tracing in large data sets of steady flow simulation experiments. This will be achieved by sophisticated preprocessing using additional memory. For further visual enhancement of the streamline we construct an implicitly defined smooth Bézier curve that is used for ray tracing. This allows us to visualize additional scalar values of the simulation as attributes to the trajectory and enables the display of high‐quality smooth curves without creating any visualization geometry and providing a good impression of the spatial situation at the same time. ACM CSS: I.3.3 Computer Graphics—Line and curve generation; I .3.7 Computer Graphics—Raytracing; G.1.2 Numerical Analysis—Spline and piecewise polynomial approximation     

Algebraic manipulation of scientific datasets

We investigate algebraic processing strategies for large numeric datasets equipped with a (possibly irregular) grid structure. Such datasets arise, for example, in computational simulations, observation networks, medical imaging, and 2-D and 3-D rendering. Existing approaches for manipulating these datasets are incomplete: The performance of SQL queries for manipulating large numeric datasets is not competitive with specialized tools. Database extensions for processing multidimensional discrete data can only model regular, rectilinear grids. Visualization software libraries are designed to process arbitrary gridded datasets efficiently, but no algebra has been developed to simplify their use and afford optimization. Further, these libraries are data dependent – physical changes to data representation or organization break user programs. In this paper, we present an algebra of gridfields for manipulating arbitrary gridded datasets, algebraic optimization techniques, and an implementation backed by experimental results. We compare our techniques to those of Geographic Information Systems (GIS) and visualization software libraries, using real examples from an Environmental Observation and Forecasting System. We find that our approach can express optimized plans inaccessible to other techniques, resulting in improved performance with reduced programming effort.     

Analysis of Long Molecular Dynamics Simulations Using Interactive Focus+Context Visualization

Analyzing molecular dynamics (MD) simulations is a key aspect to understand protein dynamics and function. With increasing computational power, it is now possible to generate very long and complex simulations, which are cumbersome to explore using traditional 3D animations of protein movements. Guided by requirements derived from multiple focus groups with protein engineering experts, we designed and developed a novel interactive visual analysis approach for long and crowded MD simulations. In this approach, we link a dynamic 3D focus+context visualization with a 2D chart of time series data to guide the detection and navigation towards important spatio‐temporal events. The 3D visualization renders elements of interest in more detail and increases the temporal resolution dependent on the time series data or the spatial region of interest. In case studies with different MD simulation data sets and research questions, we found that the proposed visual analysis approach facilitates exploratory analysis to generate, confirm, or reject hypotheses about causalities. Finally, we derived design guidelines for interactive visual analysis of complex MD simulation data.     

GPU-based remote visualization of dynamic molecular data on the web

Visualization of dynamic data from molecular dynamics simulations is crucial for understanding the functioning of molecules. Many existing visualization tools have mainly focused on supporting a single user working on a desktop computer. Technical advancements in browser features increase the potential for the development of web-based collaborative visualization tools. Although web-based molecular viewers already exist, their support for dynamic molecular data at interactive rates is lacking. To address this gap, we present an efficient web application for visualization of dynamic molecular data using WebGL that exploits HTML5 technologies like WebSockets and Web Workers. GPU-based ray casting techniques offer fast rendering times and produce images with higher visual quality. Efficient data encoding techniques are used to minimize the data transferred to the client; therefore saving bandwidth and improving the transfer times. We demonstrate the feasibility of visualizing large dynamic molecular data with more than one million atoms in the browser at interactive frame rates. Our approach allows scientists at arbitrary locations to concurrently visually analyze the same data. The interactive parameterization of the visualization can be shared among multiple clients, providing the basis for collaborative research. Moreover, the application can be employed for remote simulation monitoring on mobile devices.     

Continuous scatterplots

Scatterplots are well established means of visualizing discrete data values with two data variables as a collection of discrete points. We aim at generalizing the concept of scatterplots to the visualization of spatially continuous input data by a continuous and dense plot. An example of a continuous input field is data defined on an n-D spatial grid with respective interpolation or reconstruction of in-between values. We propose a rigorous, accurate, and generic mathematical model of continuous scatterplots that considers an arbitrary density defined on an input field on an n-D domain and that maps this density to m-D scatterplots. Special cases are derived from this generic model and discussed in detail: scatterplots where the n-D spatial domain and the m-D data attribute domain have identical dimension, 1-D scatterplots as a way to define continuous histograms, and 2-D scatterplots of data on 3-D spatial grids. We show how continuous histograms are related to traditional discrete histograms and to the histograms of isosurface statistics. Based on the mathematical model of continuous scatterplots, respective visualization algorithms are derived, in particular for 2-D scatterplots of data from 3-D tetrahedral grids. For several visualization tasks, we show the applicability of continuous scatterplots. Since continuous scatterplots do not only sample data at grid points but interpolate data values within cells, a dense and complete visualization of the data set is achieved that scales well with increasing data set size. Especially for irregular grids with varying cell size, improved results are obtained when compared to conventional scatterplots. Therefore, continuous scatterplots are a suitable extension of a statistics visualization technique to be applied to typical data from scientific computation.     

A particle system for interactive visualization of 3D flows

We present a particle system for interactive visualization of steady 3D flow fields on uniform grids. For the amount of particles we target, particle integration needs to be accelerated and the transfer of these sets for rendering must be avoided. To fulfill these requirements, we exploit features of recent graphics accelerators to advect particles in the graphics processing unit (GPU), saving particle positions in graphics memory, and then sending these positions through the GPU again to obtain images in the frame buffer. This approach allows for interactive streaming and rendering of millions of particles and it enables virtual exploration of high resolution fields in a way similar to real-world experiments. The ability to display the dynamics of large particle sets using visualization options like shaded points or oriented texture splats provides an effective means for visual flow analysis that is far beyond existing solutions. For each particle, flow quantities like vorticity magnitude and A2 are computed and displayed. Built upon a previously published GPU implementation of a sorting network, visibility sorting of transparent particles is implemented. To provide additional visual cues, the GPU constructs and displays visualization geometry like particle lines and stream ribbons.     

FIRST: a flexible and interactive resampling tool for CFD simulation data

We introduce a flexible, variable resolution tool for interactive resampling of computational fluid dynamics (CFD) simulation data on versatile grids. The tool and coupled algorithm afford users precise control of glyph placement during vector field visualization via six interactive degrees of freedom. Other important characteristics of this method include: (1) an algorithm that resamples any unstructured grid onto any structured grid, (2) handles changes to underlying topology and geometry, (3) handles unstructured grids with holes and discontinuities, (4) does not rely on any pre-processing of the data, and (5) processes large numbers of unstructured grid cells efficiently. We believe this tool to be a valuable asset in the engineer's pursuit of understanding and visualizing the underlying flow field in CFD simulation results.     

Atomistic Visualization of Mesoscopic Whole‐Cell Simulations Using Ray‐Casted Instancing

Molecular visualization is an important tool for analysing the results of biochemical simulations. With modern GPU ray casting approaches, it is only possible to render several million of atoms interactively unless advanced acceleration methods are employed. Whole‐cell simulations consist of at least several billion atoms even for simplified cell models. However, many instances of only a few different proteins occur in the intracellular environment, which can be exploited to fit the data into the graphics memory. For each protein species, one model is stored and rendered once per instance. The proposed method exploits recent algorithmic advances for particle rendering and the repetitive nature of intracellular proteins to visualize dynamic results from mesoscopic simulations of cellular transport processes. We present two out‐of‐core optimizations for the interactive visualization of data sets composed of billions of atoms as well as details on the data preparation and the employed rendering techniques. Furthermore, we apply advanced shading methods to improve the image quality including methods to enhance depth and shape perception besides non‐photorealistic rendering methods. We also show that the method can be used to render scenes that are composed of triangulated instances, not only implicit surfaces.     

Coherent Culling and Shading for Large Molecular Dynamics Visualization

Molecular dynamics simulations are a principal tool for studying molecular systems. Such simulations are used to investigate molecular structure, dynamics, and thermodynamical properties, as well as a replacement for, or complement to, costly and dangerous experiments. With the increasing availability of computational power the resulting data sets are becoming increasingly larger, and benchmarks indicate that the interactive visualization on desktop computers poses a challenge when rendering substantially more than millions of glyphs. Trading visual quality for rendering performance is a common approach when interactivity has to be guaranteed. In this paper we address both problems and present a method for high‐quality visualization of massive molecular dynamics data sets. We employ several optimization strategies on different levels of granularity, such as data quantization, data caching in video memory, and a two‐level occlusion culling strategy: coarse culling via hardware occlusion queries and a vertex‐level culling using maximum depth mipmaps. To ensure optimal image quality we employ GPU raycasting and deferred shading with smooth normal vector generation. We demonstrate that our method allows us to interactively render data sets containing tens of millions of high‐quality glyphs.     

Capabilities and limitations of 2-dimensional and 3-dimensional numerical methods in modeling the fluid flow in sudden expansion microchannels

This paper deals with computational and experimental investigations into pressure-driven flow in sudden expansion microfluidic channels. Improving the design and operation of microfluidic systems requires that the capabilities and limitations of 2-dimensional (2-D) and 3-dimensional (3-D) numerical methods in simulating the flow field in a sudden expansion microchannel be well understood. The present 2-D simulation results indicate that a flow separation vortex forms in the corner behind the sudden expansion microchannel when the Reynolds number is very low (Re∼0.1). However, the experimental results indicate that this prediction is valid only in the case of a sudden expansion microchannel with a high aspect ratio (aspect ratio >> 1). 3-D computational fluid dynamics simulations are performed to predict the critical value of Re at which the flow separation vortex phenomenon is induced in sudden expansion microchannels of different aspect ratios. The experimental flow visualization results are found to be in good agreement with the 3-D numerical predictions. The present results provide designers with a valuable guideline when choosing between 2-D or 3-D numerical simulations as a means of improving the design and operation of microfluidic devices.     

A coherent grid traversal approach to visualizing particle-based simulation data

We present an approach to visualizing particle-based simulation data using interactive ray tracing and describe an algorithmic enhancement that exploits the properties of these data sets to provide highly interactive performance and reduced storage requirements. This algorithm for fast packet-based ray tracing of multilevel grids enables the interactive visualization of large time-varying data sets with millions of particles and incorporates advanced features like soft shadows. We compare the performance of our approach with two recent particle visualization systems: one based on an optimized single ray grid traversal algorithm and the other on programmable graphics hardware. This comparison demonstrates that the new algorithm offers an attractive alternative for interactive particle visualization.     

Visual exploration of large relational data sets through 3D projections and footprint splatting

This paper discusses 3D visualization and interactive exploration of large relational data sets through the integration of several well-chosen multidimensional data visualization techniques and for the purpose of visual data mining and exploratory data analysis. The basic idea is to combine the techniques of grand tour, direct volume rendering, and data aggregation in databases to deal with both the high dimensionality of data and a large number of relational records. Each technique has been enhanced or modified for this application. Specifically, positions of data clusters are used to decide the path of a grand tour. This cluster-guided tour makes intercluster-distance-preserving projections in which data clusters are displayed as separate as possible. A tetrahedral mapping method applied to cluster centroids helps in choosing interesting cluster-guided projections. Multidimensional footprint splatting is used to directly render large relational data sets. This approach abandons the rendering techniques that enhance 3D realism and focuses on how to efficiently produce real-time explanatory images that give comprehensive insights into global features such as data clusters and holes. Examples are given where the techniques are applied to large (more than a million records) relational data sets.     

Advanced interactive visualization for CFD

New ideas are presented for the visualization of computational fluid dynamics data. These include both unsteady two-dimensional and steady three-dimensional data on either structured or unstructured grids. In addition to presenting some specific algorithm advances, considerable attention is devoted to innovative interactive probes and the appropriate choice of program architecture and internal data structure.     

Interactive time-dependent particle tracing using tetrahedraldecomposition

Streak lines and particle traces are effective visualization techniques for studying unsteady fluid flows. For real time applications, accuracy is often sacrificed to achieve interactive frame rates. Physical space particle tracing algorithms produce the most accurate results although they are usually too expensive for interactive applications. An efficient physical space algorithm is presented which was developed for interactive investigation and visualization of large, unsteady, aeronautical simulations. Performance has been increased by applying tetrahedral decomposition to speed up point location and velocity interpolation in curvilinear grids. Preliminary results from batch computations showed that this approach was up to six times faster than the most common algorithm which uses the Newton-Raphson method and trilinear interpolation. Results presented show that the tetrahedral approach also permits interactive computation and visualization of unsteady particle traces. Statistics are given for frame rates and computation times on single and multiprocessors. The benefits of interactive feature detection in unsteady flows are also demonstrated     

A visualization framework for the analysis of?neuromuscular?simulations

We present a visualization framework for exploring and analyzing data sets from biomechanical and neuromuscular simulations. These data sets describe versatile information related to the different stages of a motion analysis. In studying these data using a 3D visualization approach, interactive exploring is important, especially for supporting spatial analysis. Moreover, as these data contain many various but related elements, numerical analysis of neuromuscular simulations is complicated. Visualization techniques enhance the analysis process, thus improving the effectiveness of the experiments. Our approach allows convenient definitions of relationships between numerical data sets and 3D objects. Scientific simulation data sets appropriate for this style of analysis are present everywhere motion analysis is performed and are predominant in many clinical works. In this paper, we outline the functionalities of the framework as well as applications embedded within the OpenSim simulation platform. These functionalities form an effective approach specifically designed for the investigation of neuromuscular simulations. This claim is supported by evaluation experiments where the framework was used to analyze gaits and crouch motions.     

Visualization and User-Modeling for Browsing Personal Photo Libraries

We present a user-centric system for visualization and layout for content-based image retrieval. Image features (visual and/or semantic) are used to display retrievals as thumbnails in a 2-D spatial layout or “configuration” which conveys all pair-wise mutual similarities. A graphical optimization technique is used to provide maximally uncluttered and informative layouts. Moreover, a novel subspace feature weighting technique can be used to modify 2-D layouts in a variety of context-dependent ways. An efficient computational technique for subspace weighting and re-estimation leads to a simple user-modeling framework whereby the system can learn to display query results based on layout examples (or relevance feedback) provided by the user. The resulting retrieval, browsing and visualization can adapt to the user's (time-varying) notions of content, context and preferences in style and interactive navigation. Monte Carlo simulations with machine-generated layouts as well as pilot user studies have demonstrated the ability of this framework to model or “mimic” users, by automatically generating layouts according to their preferences.     

MGV: a system for visualizing massive multidigraphs

Describes MGV (Massive Graph Visualizer), an integrated visualization and exploration system for massive multidigraph navigation. It adheres to the visual information-seeking mantra: overview first, zoom and filter, then details on demand. MGV's only assumption is that the vertex set of the underlying digraph corresponds to the set of leaves of a pre-determined tree T. MGV builds an out-of-core graph hierarchy and provides mechanisms to plug in arbitrary visual representations for each graph hierarchy slice. Navigation from one level to another of the hierarchy corresponds to the implementation of a drill-down interface. In order to provide the user with navigation control and interactive response, MGV incorporates a number of visualization techniques like interactive pixel-oriented 2D and 3D maps, statistical displays, color maps, multi-linked views and a zoomable label-based interface. This makes the association of geographic information and graph data very natural. To automate the creation of the vertex set hierarchy for MGV, we use the notion of graph sketches. They can be thought of as visual indices that guide the navigation of a multigraph too large to fit on the available display. MGV follows the client-server paradigm and it is implemented in C and Java-3D. We highlight the main algorithmic and visualization techniques behind the tools and, along the way, point out several possible application scenarios. Our techniques are being applied to multigraphs defined on vertex sets with sizes ranging from 100 million to 250 million vertices     

Multi-block Poisson grid generator for cascade simulations

High quality computational grids can greatly enhance the accuracy of turbine and compressor cascade simulations especially when time-dependent results are sought where vortical structures are convected through the computational domain. A technique for generating periodic structured grids for cascade simulations based on the Poisson equations is described. To allow for more complex geometries, the grid can be divided into individual zones or blocks. The grids are generated simultaneously in all blocks, assuring continuity of the grid lines and their slopes across the zonal boundaries. Simple geometric rules can be employed for enforcing orthogonality at block boundaries. The method results in grids with low grid distortion by allowing both, block boundaries and grid points on physical boundaries, to move freely. Results are presented for a linear turbine and a linear compressor cascade.     

Data Visualization: Featuring Interactive Visual Analysis

Data visualization is an application‐driven field, that is always trying to satisfy its customers and to adapt to the demands, cultures, and workflows of many application areas. Therefore, it is difficult to keep focus on techniques and approaches that are not too application specific. A lot of good work on data visualization consists of single‐problem solutions, that cannot be easily merged into general‐purpose systems. In this talk, I will briefly review some current trends and issues, and identify some approaches that are common to many applications. One such approach in data visualization that has attracted interest from the early days is the detection of salient features, or patterns of interest in a data set. The main idea is to extract information at a higher level of abstraction from a mass of data, that is richer in semantics but much smaller in size, and that can help to define scenes and objects for visualization. This idea was pioneered in areas such as flow visualization, but is now more widely applied. It is often considered to be necessity to keep up with the ever rapidly increasing size of data sets, and the demand for interactivity in data visualization and analysis. Another generic approach in data visualization is called interactive visual analysis (TVA), consisting of a strongly interactive multiple‐linked‐view interfaces with integrated, powerful data analysis techniques taken from statistical analysis, pattern recognition, machine learning, and other fields. This is built on the assumptions that a single 2D or 3D visualization is often not enough, and spatial views can be augmented with abstract, derived data spaces; that strong interaction helps to promote insight; and that a better balance is needed between human visual inspection and computer‐based analysis and reasoning. Interestingly, an IVA interface can serve not only as an environment for exploration of low‐level data, but also for defining the high‐level features to be extracted, that should summarize the essence of the data. The high‐level features are usually highly application specific, and can only be found using theories from the application domains. The big challenge is to create environments for general purpose visual data analysis, and yet allow users to introduce advanced theories and methods from many application domains. The trend towards more integration in data visualization will be illustrated with cross‐links between very different areas, such as medical and flow visualization, and the combined use of techniques from scientific visualization and information visualization, and the absorption of other data analysis techniques. Also, historic and contemporary examples of feature extraction and interactive visual analysis will be shown.     

Visualizing multiphysics,fluid-structure interaction phenomena in intracranial aneurysms

This work presents recent advances in visualizing multi-physics, fluid-structure interaction (FSI) phenomena in cerebral aneurysms. Realistic FSI simulations produce very large and complex data sets, yielding the need for parallel data processing and visualization. Here we present our efforts to develop an interactive visualization tool which enables the visualization of such FSI simulation data. Specifically, we present a ParaView–NekTar interface that couples the ParaView visualization engine with NekTar’s parallel libraries, which are employed for the calculation of derived fields in both the fluid and solid domains with spectral accuracy. This interface allows the flexibility of independently choosing the resolution for visualizing both the volume data and the surface data from each of the solid and fluid domains, which significantly facilitates the visualization of complex structures under large deformations. The animation of the fluid and structure data is synchronized in time, while the ParaView–NekTar interface enables the visualization of different fields to be superimposed, e.g. fluid jet and structural stress, to better understand the interactions in this multi-physics environment. Such visualizations are key towards elucidating important biophysical interactions in health and disease, as well as disseminating the insight gained from our simulations and further engaging the medical community in this effort of bringing computational science to the bedside.