Scientific Visualization Final Report

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Jeffery Wright
5 years ago
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1. Goal Scientific Visualization Final Report Suqin Zeng 00746736 This project is aimed to simulate a dynamic particle system, visualizing the density of the particles in real time. 2.

The strength of VTK is it provides many useful build-in features such as color map, interactive camera, and various UI components. 2.

1 1. Goal Scientific Visualization Final Report Suqin Zeng This project is aimed to simulate a dynamic particle system, visualizing the density of the particles in real time. 2. System implementation 2.1 Software VTK is used to implement this project. The strength of VTK is it provides many useful build-in features such as color map, interactive camera, and various UI components. 2.2 Data Generator The particle system is comprised of several particle emitters, each moving randomly while emitting particles at the same time. The data to be visualized are the particles in the space, each particle contains the position information (x, y, z), and a scalar value indicating the density in the neighborhood. The method to calculate density will be discussed afterward. 2.3 Visualization strategy Each particle is rendered as a little plane with texture; color is set according to the density value (using a color map). To achieve the effect of visually 3D particle from all perspective, the normal of each particle plane is updating simultaneously when the camera is being rotated or translated, so that it is always facing the camera. Figure-1 particle representation: (left) overview; (right) particle texture Before I adopted this method, I tried to render the particles with elementary 3d models, such as

sphere and cube. However, these turned out to be much slower than using plane (the former has much more faces), and failed or had very bad effect in applying texture.

By moving the 7 handles in each face and the center of the control box, user could choose the interest region.

2 sphere and cube. However, these turned out to be much slower than using plane (the former has much more faces), and failed or had very bad effect in applying texture. Figure-2 effect of using cube to represent particle 2.4 User control Users have 4 controls over the system. [1] Interest region. By moving the 7 handles in each face and the center of the control box, user could choose the interest region. Particles inside the box will be colored while the others stay gray. Particles that are outside the interest region could be hidden by pressing o from the keyboard. Figure-3 user control [1] choose interest region [2] Perspective. By dragging the mouse, user could rotate, translate and zoom in/out the

Using a slider, user could change the moving speed of particles as

3 camera, so as to view the space in various perspectives. Figure-4 user control [2] change perspective [3] Speed Control. Using a slider, user could change the moving speed of particles as well as the emitters. Figure-5 user control [3] speed control. (left) slow; (right) fast

[4] Particle quantity. Using a slider, user could control the number of existing particles each emitter has. Figure-6 user control [4] particle quantity control.

4 [4] Particle quantity. Using a slider, user could control the number of existing particles each emitter has. Figure-6 user control [4] particle quantity control. (left) 1,000 particles; (right) 15,000 particles 2.5 Density calculation The interest region is divided into N*N*N unit cubes. Each cube has a counter which records the number of particles in it. The density of a cube is calculated as the weighted sum of its own counter and the counters of its 8 nearest neighbors. Particles within a cube are assigned the density value of the cube. 3. Result Analysis The frame rate of the program is exponentially related to N, which is the number of subdivisions along an axis. As revealed in the following table. N step time cost (sec) Table-1 N and time cost (processing 5000 particles); experiment environment: Windows 7 64-bit with Intel Core 2 Duo T GHz In this project, I choose N = 80, given the ideal frame rate to be 30. The update rate of the particle system is much lower than the render rate, so it turns out that the particle quantity does not affect the overall frame rate apparently. 4. Expansion This system can be adapted to show the density of any group of points in 3D space. It is useful especially for locating abnormal places where the density is different from other regions. Such as finding the sparse area in a point cloud, which is seemly evenly distributed.

5 Figure-7 density visualization on static point cloud. (left) without density visualization (right) with density visualization 5. Conclusion This project simulated a dynamic particle system, visualizing the density of the particles in real time. It provides user controls for changing perspective, interest region as well as particle quantity and speed. 5.1 Future work [1] Currently the method to calculate the density value is just an approximation of the real density. A more precise method should be calculating a sphere region centered at each particle, it is not adopted for low time efficiency. be devised in the future. A more optimized version of calculating precise density could [2] Adaption to visualize invisible qualities, such as temperature, pressure or force tension could also be researched.

In this tutorial, you will create a scene with sandman dispersing in sand, as shown in in the image below.

Particle Flow In this tutorial, you will create a scene with sandman dispersing in sand, as shown in in the image below. Creating the Project Folder 1. Create a project folder with the name c17_tut1 at