The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.11 - November (2011 vol.17)
pp: 1574-1586
C. Brownlee , Sci. Comput. & Imaging Inst., Univ. of Utah, Salt Lake City, UT, USA
V. Pegoraro , Lehrstuhl fur Computergraphik, Univ. des Saarlandes, Saarbrucken, Germany
S. Shankar , One Gateway Center, TerraSim, Inc., Pittsburgh, PA, USA
Patrick S. McCormick , Los Alamos Nat. Labs., Los Alamos, NM, USA
C. D. Hansen , Sci. Comput. & Imaging Inst., Univ. of Utah, Salt Lake City, UT, USA
ABSTRACT
Understanding fluid flow is a difficult problem and of increasing importance as computational fluid dynamics (CFD) produces an abundance of simulation data. Experimental flow analysis has employed techniques such as shadowgraph, interferometry, and schlieren imaging for centuries, which allow empirical observation of inhomogeneous flows. Shadowgraphs provide an intuitive way of looking at small changes in flow dynamics through caustic effects while schlieren cutoffs introduce an intensity gradation for observing large scale directional changes in the flow. Interferometry tracks changes in phase-shift resulting in bands appearing. The combination of these shading effects provides an informative global analysis of overall fluid flow. Computational solutions for these methods have proven too complex until recently due to the fundamental physical interaction of light refracting through the flow field. In this paper, we introduce a novel method to simulate the refraction of light to generate synthetic shadowgraph, schlieren and interferometry images of time-varying scalar fields derived from computational fluid dynamics data. Our method computes physically accurate schlieren and shadowgraph images at interactive rates by utilizing a combination of GPGPU programming, acceleration methods, and data-dependent probabilistic schlieren cutoffs. Applications of our method to multifield data and custom application-dependent color filter creation are explored. Results comparing this method to previous schlieren approximations are finally presented.
INDEX TERMS
interferometry, computational fluid dynamics, computer graphic equipment, coprocessors, data visualisation, schlieren approximations, physically based interactive flow visualization, schlieren experimental techniques, interferometry experimental techniques, fluid flow, computational fluid dynamics, shadowgraph, flow dynamics, time varying scalar fields, GPGPU programming, acceleration methods, data dependent probabilistic schlieren cutoffs, application dependent color filter creation, Optical interferometry, Optical filters, Refractive index, Image color analysis, Laser beams, Data visualization, Light sources, flow visualization., Scalar field data, GPUs and multicore architectures
CITATION
C. Brownlee, V. Pegoraro, S. Shankar, Patrick S. McCormick, C. D. Hansen, "Physically-Based Interactive Flow Visualization Based on Schlieren and Interferometry Experimental Techniques", IEEE Transactions on Visualization & Computer Graphics, vol.17, no. 11, pp. 1574-1586, November 2011, doi:10.1109/TVCG.2010.255
REFERENCES
[1] M. Anyoji and M. Sun, “Computer Analysis of the Schlieren Optical Setup,” Proc. SPIE, vol. 6279, pp. 62790M, 2007.
[2] B. Atcheson, I. Irkhe, W. Heidrich, A. Tevs, D. Bradley, M. Magnor, and H.-P. Seidel, “Time Resolved 3d Capture of Non-Stationary Gas Flows,” ACM Trans. Graphics, vol. 25, no. 5, p. 132, Dec. 2008.
[3] M. Born, E. Wolf, and A.B. Bhatia, Principles of Optics, seventh ed. Cambridge Univ. Press, 1999.
[4] D.K. Brayford, “Rendering of Polarized Subsurface Light Scattering,” PhD thesis, Univ. of Manchester, 2006.
[5] C. Brownlee, V. Pegoraro, P.S. McCormick, S. Shankar, and C.D. Hansen, “Physically-Based Interactive Schlieren Flow Visualization,” Proc. IEEE Pacific Visualization Symp., pp. 145-152, 2010.
[6] J.H. Chen, A. Choudhary, B. de Supinski, M. DeVries, E.R. Hawkes, S. Klasky, W.K. Liao, K.L. Ma, J. Mellor-Crummey, N. Podhorszki, R. Sankaran, S. Shende, and C.S. Yoo, “Terascale Direct Numerical Simulations of Turbulent Combustion Using s3d,” Computational Science and Discovery, vol. 2, pp. 1-3, 2009.
[7] P.E. Ciddor, “Refractive Index of Air: New Equations for the Visible and near Infrared,” Applied Optics, vol. 35, pp. 15-66, 1996.
[8] K. Gaither, “Visualization's Role in Analyzing Computational Fluid Dynamics Data,” IEEE Computer Graphics, vol. 24, no. 3, pp. 13-15, May/June 2004.
[9] D. Gutierrez, F.J. Seron, O. Anson, and A. Munoz, “Chasing the Green Flash: A Global Illumination Solution for Inhomogeneous Media,” Proc. Spring Conf. Computer Graphics , pp. 97-105, 2004.
[10] I. Ihrke, G. Ziegler, A. Tevs, C. Theobalt, M. Magnor, and H.-P. Seidel, “Eikonal Rendering: Efficient Light Transport in Refractive Objects,” ACM Trans. Graphics (SIGGRAPH '07), vol. 59, pp. 1-9, Aug. 2007.
[11] H.W. Jensen, “Global Illumination Using Photon Maps,” Proc. Seventh Eurographics Workshop Rendering, pp. 21-30, 1996.
[12] H.W. Jensen and P.H. Christensen, “Efficient Simulation of Light Transport in Scenes with Participating Media Using Photon Maps,” Proc. ACM SIGGRAPH '98, pp. 311-320, 1998.
[13] C. Johnson, R. Ross, S. Ahern, J. Ahrens, W. Bethel, K.-L. Ma, M. Papka, J. van Rosendale, H.-W. Shen, and J. Thomas, “Visualization and Knowledge Discovery: Report from the Doe/Ascr,” Proc. Workshop Visual Analysis and Data Exploration at Extreme Scale, Oct. 2007.
[14] F.T. Johnson, E.N. Tinoco, and N.J. Yu, “Thirty Years of Development and Application of Cfd at Boeing Commercial Airplanes, Seattle,” Computers and Fluids, vol. 34, pp. 1115-1117, 2005.
[15] S. Liu, J.C. Hewson, J.H. Chen, and H. Pitsch, “Effects of Strain Rate on High-Pressure Nonpremixed N-Heptane Autoignition in Counterflow,” Combustion and Flame, vol. 137, pp. 320-339, May 2004.
[16] T.J. McIntyre, I. Lourel, T.N. Eichmann, R.G. Morgan, P.A. Jacobs, and A.I. Bishop, “An Experimental Expansion Tube Study of the Flow over a Toroidal Ballute,” J. Spacecraft and Rockets, vol. 41, no. 5, pp. 716-725, 2004.
[17] W. Merzkirch, Flow Visualization. Academic Press, 1987.
[18] NVIDIA, CUDA Programming Guide, http://developer.nvidia. com/objectcuda.html , 2009.
[19] V. Pegoraro and S.G. Parker, “Physically-Based Realistic Fire Rendering,” Proc. Second Eurographics Workshop Natural Phenomena, pp. 51-59, 2006.
[20] G. Settles, Schlieren and Shadowgraph Techniques, Visualizing Phenomena in Transparent Media. Springer, 2001.
[21] G. Settles, “High-Speed Imaging of Shock Waves, Explosions and Gunshots,” Am. Scientist, vol. 94, no. 1, pp. 22-31, 2006.
[22] A.J. Smits and T.T. Lim, Flow Visualization: Techniques and Examples. Imperial College Press, 2000.
[23] M. Sun, “Computer Modeling of Shadowgraph Optical Setup,” Proc. SPIE, vol. 6279, pp. 62790L, 2007.
[24] X. Sun, K. Zhou, E. Stollnitz, J. Shi, and B. Guo, “Interactive Relighting of Dynamic Refractive Objects,” ACM Trans. Graphics, vol. 27, no. 3, pp. 35:1-9, 2008.
[25] N.A. Svakhine, Y. Jang, D. Ebert, and K. Gaither, “Illustration and Photography Inspired Visualization of Flows and Volumes,” Proc. IEEE Visualization, pp. 687-694, 2005.
[26] L.A. Vasil'ev, Schlieren Methods. Keter, Inc., 1971.
[27] F.J. Weinberg, Optics of Flames. Butterworths, 1963.
[28] L.A. Yates, “Images Constructed from Computed Flow Fields,” Am. Inst. of Aeronautics and Astronautics, vol. 31, no. 10, pp. 1877-1884, 1993.
23 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool