Flow Visualization Research For Space Tele-Science Experiment

Visualization of flow field is a subject that urgently needs to be solved in both scientific research and engineer practice. Since there are complex topology structures in the flow data and the data always contain various attributes such as magnitude, direction, position and so on, it is a tough problem for researchers to visualize the information comprehensively. Until now, there is no method publicly affirmed as generally applicable in this field. With the application background for Tele-Science Experiment Information Enhancement Research of National 863 Project, the texture-based and feature-based flow visualization methods are studied in the thesis. The 2D texture-based flow visualization algorithm and its performance enhancement, the features detection and extraction in 3D field, the placement strategy of 3D streamline, and the credibility of the visualization algorithm, are deeply studied in the thesis.The main innovations and research results are as following:1) For the 2D flow visualization, a particle-texture blending based visualization method is presented. In the method, block texture advection instead of pixel texture advection of the traditional LIC method is adopted to enhance the performance, and dynamic flow visualization is obtained. Experiment results indicate that the method is independent of the complexity of the flow field data and is of generality. It is superior in performance compared with LIC method. It possesses higher contrast and clearer physical meaning than that of IBFV method.2) For the 3D flow visualization, a 3D streamline generation method is presented. The method is comprised of three processes. Firstly, based on the fast detection of critical points, the critical points are classified according to the eigenvalues of their Jacobian Matirx, and the match between the critical points and the seed templates is performed. Secondly, the seeds points are ordered in priority, and streamlines are generated in physical space. Finally, in image space, the distance between streamlines is controlled by the preset threshold value, and the nearest streamline to the observer is hold according to the depth detection, thus the display clarity is ensured. Simulation results indicate that the method can solve both the feature extraction and the clarity expression problems in flow visualization.3) For the feature extraction problem, a theorem for the existence of critical points in flow fields is proposed and proved. And a fast detection algorithm of critical points is presented based on the theory. The experiment results indicate that the algorithm can extract all the critical points in the flow field. 4) The credibility analysis of the methods presented in this thesis is proposed. From the two aspects of error analysis and result validation, the credibility analyses of both particle-texture blending method and the 3D feature extraction streamline method are deeply studied. In the process of error analyses, an estimation formula of error remaining for the bilinear interpolation function is put forward and proved. From the theory analysis and test result, the credibility of the method is verified.Based on the study above, a visualization system for the information enhancement in space crystal growth experiment is designed and implemented. The temperature distribution and the flow movement in the crystal stove are vividly displayed. The performance of the system is fully affirmed and well evaluated by the user.