Microscale flow visualization

Advances in microfluidic and nanofluidic technologies have been paralleled by advances in methods for direct optical measurement of transport phenomena on these scales. A variety of methods for microscale flow visualization have appeared and evolved since the late 1990s. These methods and their applications to date are reviewed here in detail, and in context of the both the fundamental phenomena they exploit and the fundamental phenomena they are applied to measure. Where possible, links to macroflow visualization methods are established, and the physical mechanisms underlying these methods are explained.     

Comparative flow visualization

There are many situations where one needs to compare two or more data sets. It may be to compare different models, different resolutions, differences in algorithms, different experimental results, etc. There is therefore a need for comparative visualization tools to help analyze the differences. This paper focuses on comparative visualization tools for analyzing flow or vector data sets. The techniques presented allow one to compare individual streamlines and stream ribbons as well as a dense field of streamlines. These comparison methods can also be used to study differences in vortex cores that are represented as polylines.     

AGP 2x VS AGP 4x

如今的3D游戏场景,除了运用大型纹理材质进行贴图,还不断地提高分辨率和采用32位色深。就算我们都已经升级为PⅢ系统,大内存和更快的3D加速卡,都仍然不能真正地解决问题,其中的一个重要原因就是性能瓶颈:想象一下,假设你跑完1万公里的马拉松比赛,正需要大量的清新空气来帮助呼吸,却只能用一根直径只有几毫米的吸管呼吸,那即使你每秒提升呼吸的次数也没什么作用。 在AGP 2x接口中,总线为 32bit,运行在 66MHz工作频率,由于在单一周期内的上升和下降都传输数据,所以能传送理论上 66MHz×2x 32bit/8=528MB/s的数据流量。而AGP 4x拥有两倍于AGP 2x的带宽,可以达到1056MB/s的数据传输率。照此来说,性能提升一倍,那么瓶颈问题应该解决了(马拉松选手的口里塞了N根吸管,呼吸问题暂时得以解决)。在下面的性能测试中,AGP 2x VS AGP 4x:     

Flodar: flow visualization of network traffic

The author and his colleagues at the National Security Agency designed an application called Flodar (short for Flow Radar) that monitors the flow of network traffic. The techniques and visuals used in Flodar can apply to a variety of applications. While many flow visualizations concentrate on the path of network traffic, this system monitors the status of individual servers within the system. In their particular system, they need to monitor two types of servers: those that send information at semi-regular intervals and those that receive this information and store it temporarily, waiting for users to read or process the information within a certain time. They are not as concerned with the path the data takes to get from the sending server to the storage server. They are more concerned with ensuring the sender transmits regularly and that the information on the storage server is processed before being overwritten. Therefore, monitoring the system's timeliness remains the primary objective for Flodar     

Minimally immersive flow visualization

This paper describes a minimally immersive interactive system for flow visualization of multivariate volumetric data. The system, SFA, uses perceptually motivated rendering to increase the quantity and clarity of information perceived. Proprioception, stereopsis, perceptually motivated shape visualization, and three-dimensional interaction are combined in SFA to allow the three-dimensional volumetric visualization, manipulation, navigation, and analysis of multivariate, time-varying flow data     

Smoke surfaces: an interactive flow visualization technique inspired by real-world flow experiments

Smoke rendering is a standard technique for flow visualization. Most approaches are based on a volumetric, particle based, or image based representation of the smoke. This paper introduces an alternative representation of smoke structures: as semi-transparent streak surfaces. In order to make streak surface integration fast enough for interactive applications, we avoid expensive adaptive retriangulations by coupling the opacity of the triangles to their shapes. This way, the surface shows a smoke-like look even in rather turbulent areas. Furthermore, we show modifications of the approach to mimic smoke nozzles, wool tufts, and time surfaces. The technique is applied to a number of test data sets.     

低开销的海面模型

传统的海面模拟从提高局部海浪效果的角度出发,通过大量的类正弦波或噪声波的叠加来模拟连续的海浪,导致算法复杂度很高。针对该问题,提出了一种海面模拟模型LOSM（Low-consumption Ocean Simulation Model）,该模型分别对海浪和海洋整体运动进行独立建模,通过将模型函数进行叠加的方法,将两者有机地结合在一起建立海面模型;设计了海面模拟算法,采用凹凸映射方法进行海浪的模拟,采用少量小波幅的正弦函数叠加的方法模拟海洋的整体运动。实验结果表明,该方法不仅视觉效果良好,而且可节省大量的资源。     

An information-theoretic framework for flow visualization

The process of visualization can be seen as a visual communication channel where the input to the channel is the raw data, and the output is the result of a visualization algorithm. From this point of view, we can evaluate the effectiveness of visualization by measuring how much information in the original data is being communicated through the visual communication channel. In this paper, we present an information-theoretic framework for flow visualization with a special focus on streamline generation. In our framework, a vector field is modeled as a distribution of directions from which Shannon's entropy is used to measure the information content in the field. The effectiveness of the streamlines displayed in visualization can be measured by first constructing a new distribution of vectors derived from the existing streamlines, and then comparing this distribution with that of the original data set using the conditional entropy. The conditional entropy between these two distributions indicates how much information in the original data remains hidden after the selected streamlines are displayed. The quality of the visualization can be improved by progressively introducing new streamlines until the conditional entropy converges to a small value. We describe the key components of our framework with detailed analysis, and show that the framework can effectively visualize 2D and 3D flow data.     

Straightening tubular flow for side-by-side visualization

Flows through tubular structures are common in many fields, including blood flow in medicine and tubular fluid flows in engineering. The analysis of such flows is often done with a strong reference to the main flow direction along the tubular boundary. In this paper we present an approach for straightening the visualization of tubular flow. By aligning the main reference direction of the flow, i.e., the center line of the bounding tubular structure, with one axis of the screen, we are able to natively juxtapose (1.) different visualizations of the same flow, either utilizing different flow visualization techniques, or by varying parameters of a chosen approach such as the choice of seeding locations for integration-based flow visualization, (2.) the different time steps of a time-dependent flow, (3.) different projections around the center line , and (4.) quantitative flow visualizations in immediate spatial relation to the more qualitative classical flow visualization. We describe how to utilize this approach for an informative interactive visual analysis. We demonstrate the potential of our approach by visualizing two datasets from two different fields: an arterial blood flow measurement and a tubular gas flow simulation from the automotive industry.     

Virtual rheoscopic fluids for flow visualization

Physics-based flow visualization techniques seek to mimic laboratory flow visualization methods with virtual analogues. In this work we describe the rendering of a virtual rheoscopic fluid to produce images with results strikingly similar to laboratory experiments with real-world rheoscopic fluids using products such as Kalliroscope. These fluid additives consist of microscopic, anisotropic particles which, when suspended in the flow, align with both the flow velocity and the local shear to produce high-quality depictions of complex flow structures. Our virtual rheoscopic fluid is produced by defining a closed-form formula for the orientation of shear layers in the flow and using this orientation to volume render the flow as a material with anisotropic reflectance and transparency. Examples are presented for natural convection, thermocapillary convection, and Taylor-Couette flow simulations. The latter agree well with photographs of experimental results of Taylor-Couette flows from the literature.     

Interactive scientific visualization of fluid flow

Examples of scientific visualization techniques used for the interactive exploration of very large data sets from supercomputer simulations of fluid flow are presented. Interactive rendering of images from simulations of grids of 2 million or more computational zones are required to drive high-end graphics workstations to their limits with 2-D data. The author presents one such image and discusses interactive steering of 2-D flow simulations, a phenomenon now possible with grids of half a million computational zones. He uses a simulation of compressible turbulence on a grid of 134 million computational zones to set the scale for discussing interactive 3-D visualization techniques. A concept for a gigapixel-per-second video wall, or gigawall, which could be built with present technology to meet the demands of interactive visualization of the data sets that will be produced by the next generation of supercomputers, is discussed     

The NRL layered ocean model

We describe the portable scalable implementation of the NRL Layered Ocean Model (NLOM). Scalability is based primarily on the tiled data parallel parallel programming paradigm. This is sufficiently general that the actual technique used on a given machine to obtain scalability can be selected at compile time from: (i) data parallel, (ii) SPMD message passing, (iii) autotasking, or (iv) SPMD message passing between multi-processor autotasked systems. The code is thus portable onto all machine types likely to be used by ocean modelers.     

一种视点相关的海浪网格模型

在海浪模拟中,通过对两种常用网格化模型(基于随机采样点的网格化和基于固定采样点的网格化)的实验分析,给出了一种视点相关的海浪网格模型.在此基础上,运用纹理映射技术较好地模拟了大范围内的海浪生成,在保证较好的图像质量的同时提高了绘制效率.     

A mass conservative flow field visualization method

This paper introduces a new technique for computer visualization of three-dimensional flow fields. The most powerful feature of this technique is that the streamlines and stream surface are generated by mass conservative interpolation schemes. Interpolation is an important topic in flow visualization because CFD velocity fields are defined at a discrete location in space. Interpolation errors are more significant than those arising from numerical integration. The main draw-back of conventional trilinear interpolation of velocity is that it is not mass conservative. Failure to conserve mass can produce errors which can not be eliminated by reducing the integration step. A significant feature of the relationship between the velocity field and the stream functions is that it implies conservation of mass. So a mass conservative interpolation scheme is developed using a stream function, which is obtained by solving the partial differential equation in the local cell and approximated by a cluster of stream surfaces. Then the streamline can be traced using numerical techniques with mass conservative interpolation and the stream surface is directly calculated by slicing the stream function. The result is more accurate because we replace the polygoned tiling of streamlines by mass conservative stream surface generation. Results presented here compare the performance of the new method to the trilinear interpolation scheme and demonstrate its effectiveness.     

Interactive visualization and analysis of transitional flow

A stand-alone visualization application has been developed by a multi-disciplinary, collaborative team with the sole purpose of creating an interactive exploration environment allowing turbulent flow researchers to experiment and validate hypotheses using visualization. This system has specific optimizations made in data management, caching computations, and visualization allowing for the interactive exploration of datasets on the order of 1TB in size. Using this application, the user (co-author Calo) is able to interactively visualize and analyze all regions of a transitional flow volume, including the laminar, transitional and fully turbulent regions. The underlying goal of the visualizations produced from these transitional flow simulations is to localize turbulent spots in the laminar region of the boundary layer, determine under which conditions they form, and follow their evolution. The initiation of turbulent spots, which ultimately lead to full turbulence, was located via a proposed feature detection condition and verified by experimental results. The conditions under which these turbulent spots form and coalesce are validated and presented.     

ISA and IBFVS: image space-based visualization of flow on surfaces

We present a side-by-side analysis of two recent image space approaches for the visualization of vector fields on surfaces. The two methods, image space advection (ISA) and image-based flow visualization for curved surfaces (IBFVS) generate dense representations of time-dependent vector fields with high spatio-temporal correlation. While the 3D vector fields are associated with arbitrary surfaces represented by triangular meshes, the generation and advection of texture properties is confined to image space. Fast frame rates are achieved by exploiting frame-to-frame coherency and graphics hardware. In our comparison of ISA and IBFVS, we point out the strengths and weaknesses of each approach and give recommendations as to when and where they are best applied.     

Gremlin: an interactive visualization model for analyzing genomic rearrangements

In this work we present, apply, and evaluate a novel, interactive visualization model for comparative analysis of structural variants and rearrangements in human and cancer genomes, with emphasis on data integration and uncertainty visualization. To support both global trend analysis and local feature detection, this model enables explorations continuously scaled from the high-level, complete genome perspective, down to the low-level, structural rearrangement view, while preserving global context at all times. We have implemented these techniques in Gremlin, a genomic rearrangement explorer with multi-scale, linked interactions, which we apply to four human cancer genome data sets for evaluation. Using an insight-based evaluation methodology, we compare Gremlin to Circos, the state-of-the-art in genomic rearrangement visualization, through a small user study with computational biologists working in rearrangement analysis. Results from user study evaluations demonstrate that this visualization model enables more total insights, more insights per minute, and more complex insights than the current state-of-the-art for visual analysis and exploration of genome rearrangements.     

Toward a perceptual theory of flow visualization.

Currently, most researchers in visualization pay very little attention to vision science. The exception is when the effective use of color is the subject. Little research in flow visualization includes a discussion of the related perceptual theory. Nor does it include an evaluation of effectiveness of the display techniques that are generated. This is so, despite Laidlaw's paper showing that such an evaluation is relatively straightforward. Of course, it's not always necessary to relate visualization research to perceptual theory. If the purpose of the research is to increase the efficiency of an algorithm, then the proper test is one of efficiency, not of perceptual validity. But when a new representation of data is the subject of research, addressing how perceptually effective it is - either by means of a straightforward empirical comparison with existing methods or analytically, relating the new mapping to perceptual theory - should be a matter of course. A strong interdisciplinary approach, including the disciplines of perception, design, and computer science will produce better science and better design in that empirically and theoretically validated visual display techniques will result.     

3D flow features visualization via fuzzy clustering

A key approach to visualizing a flow field is to emphasize regions with significant behavior. However, it is difficult to give concrete criteria for classifying feature regions. In this paper, we use a novel framework in which fuzzy sets are used to determine flow features: Fuzzy relationships assess structural properties of features. A fuzzy c-means-like clustering algorithm is used to evaluate the importance of each voxel. Our approach can be readily modified with new fuzzy relationships describing other features of interest to users. We use a multi-resolution approach which displays structural features in greater detail, and represents the background by coarse-grained information. Experiments on synthetic and real datasets show that our framework can highlight significant aspects of the whole flow while avoiding occlusion and clutter. Interactive performance is achieved via a GPU implementation.