Flow Visualization Based on Enhanced Streamline Line Integral Convolution

Authors

Han Min, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116023;
Haichao Zhang, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116023;
Maosong Bian, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116023;
Danchen Zheng, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116023;

Abstract

Abstract: In order to show the flow information clearly and reduce the calculation of linear integral convolution, an enhanced streamline linear integral convolution algorithm was proposed. The generation of streamlines were improved. Critical points were detected and the points’ area with a gradient fill was generated. Combined two integration methods in different areas, the integration step was updated adaptively. Utilizing the parallelism of GPU and GLSL (OpenGL shading language), the algorithm further improved the sharpness of the output image. Experiments show that the improved linear integral convolution algorithm posses both the speedability and the precision. And the flow visualization of the river and hurricane with this improved method can show the flow field information intuitively.

Recommended Citation

Min, Han; Zhang, Haichao; Bian, Maosong; and Zheng, Danchen (2020) "Flow Visualization Based on Enhanced Streamline Line Integral Convolution," Journal of System Simulation: Vol. 28: Iss. 12, Article 8.
DOI: 10.16182/j.issn1004731x.joss.201612008
Available at: https://dc-china-simulation.researchcommons.org/journal/vol28/iss12/8

First Page

2933

Revised Date

2015-07-09

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201612008

Last Page

2938

CLC

TP391

Recommended Citation

Han Min, Zhang Haichao, Bian Maosong, Zheng Danchen. Flow Visualization Based on Enhanced Streamline Line Integral Convolution[J]. Journal of System Simulation, 2016, 28(12): 2933-2938.

DOI

10.16182/j.issn1004731x.joss.201612008