This Article 
 Bibliographic References 
 Add to: 
A New Line Integral Convolution Algorithm for Visualizing Time-Varying Flow Fields
April-June 1998 (vol. 4 no. 2)
pp. 98-108

Abstract—New challenges on vector field visualization emerge as time-dependent numerical simulations become ubiquitous in the field of computational fluid dynamics (CFD). To visualize data generated from these simulations, traditional techniques, such as displaying particle traces, can only reveal flow phenomena in preselected local regions and, thus, are unable to track the evolution of global flow features over time. This paper presents a new algorithm, called UFLIC (Unsteady Flow LIC), to visualize vector data in unsteady flow fields. Our algorithm extends a texture synthesis technique, called Line Integral Convolution (LIC), by devising a new convolution algorithm that uses a time-accurate value scattering scheme to model the texture advection. In addition, our algorithm maintains the coherence of the flow animation by successively updating the convolution results over time. Furthermore, we propose a parallel UFLIC algorithm that can achieve high load-balancing for multiprocessor computers with shared memory architecture. We demonstrate the effectiveness of our new algorithm by presenting image snapshots from several CFD case studies.

[1] D.A. Lane,“Visualization of time-dependent flow fields,” Proc. Visualization’93, IEEE Press, pp. 32-38.
[2] D.A. Lane, "Visualizing Time-Varying Phenomena in Numerical Simulations of Unsteady Flows," Proc. 34th Aerospace Science Meeting and Exhibit, AIAA-96-0048, 1996.
[3] B. Cabral and L.C. Leedom, "Imaging Vector Fields Using Line Integral Convolution," Computer Graphics (SIGGRAPH '93 Proc.), pp. 263-272, 1993.
[4] L.K. Forsell and S.D. Cohen, Using Line Integral Convolution for Flow Visualization: Curvilinear Grids, Variable-Speed Animation, and Unsteady Flows IEEE Trans. Visualization and Computer Graphics, vol. 1, no. 2, pp. 133-141, June 1995.
[5] H.-W. Shen and D.L. Kao, “Uflic: A Line Integral Convolution Algorithm for Visualizing Unsteady Flows,” Proc. Visualization '97, pp. 317-322, 1997.
[6] D. Stalling and H.-C. Hege, “Fast and Resolution Independent Line Integral Convolution,” SIGGRAPH 95 Conf. Proc., pp. 249-256, Aug. 1995.
[7] H.-W. Shen, C. Johnson, and K.-L. Ma, “Visualizing Vector Fields Using Line Integral Convolution and Dye Advection,” Proc. IEEE 1996 Symp. Volume Visualization, pp. 63-70, 1996.
[8] A. Okada and D.L. Kao, "Enhanced Line Integral Convolution With Flow Feature Detection," Proc. IS&T/SPIE Electronic Imaging '97, pp. 206-217, 1997.
[9] M.-H. Kiu and D.C. Banks, “Multi-Frequency Noise for LIC,” Proc. Visualization '96, 1996.
[10] B. Jobard and W. Lefer, The Motion Map: Efficient Computation of Steady Flow Animations Proc. IEEE Visualization '97, R. Yagel and H. Hagen, eds., pp. 323-328, Oct. 1997.
[11] M. Zöckler, D. Stalling, and H.-C. Hege, "Parallel Line Integral Convolution," Proc. First Eurographics Workshop Parallel Graphics and Visualization, pp. 111-128, Sept. 1996.
[12] J.J. van Wijk, “Spot Noise-Texture Synthesis for Data Visualization,” Computer Graphics (SIGGRAPH '91 Proc.), T.W. Sederberg, ed., vol. 25, pp. 309-318, July 1991.
[13] W. de Leeuw and J.J. van Wijk, “Enhanced Spot Noise for Vector Field Visualization,” Proc. IEEE Visualization '95, pp. 233-239, 1995.

Index Terms:
Flow visualization, vector field visualization, image convolution, line integral convolution, flow animation, unsteady flows, texture synthesis, parallel algorithm.
Han-Wei Shen, David L. Kao, "A New Line Integral Convolution Algorithm for Visualizing Time-Varying Flow Fields," IEEE Transactions on Visualization and Computer Graphics, vol. 4, no. 2, pp. 98-108, April-June 1998, doi:10.1109/2945.694952
Usage of this product signifies your acceptance of the Terms of Use.