article

Inverse Modelling of Incompressible Gas Flow in Subspace

Authors:

Aimin HaoAuthors Info & Claims

Computer Graphics Forum, Volume 36, Issue 6

Pages 100 - 111

https://doi.org/10.1111/cgf.12861

Published: 01 September 2017 Publication History

Abstract

This paper advocates a novel method for modelling physically realistic flow from captured incompressible gas sequence via modal analysis in frequency-constrained subspace. Our analytical tool is uniquely founded upon empirical mode decomposition EMD and modal reduction for fluids, which are seamlessly integrated towards a powerful, style-controllable flow modelling approach. We first extend EMD, which is capable of processing 1D time series but has shown inadequacies for 3D graphics earlier, to fit gas flows in 3D. Next, frequency components from EMD are adopted as candidate vectors for bases of modal reduction. The prerequisite parameters of the Navier-Stokes equations are then optimized to inversely model the physically realistic flow in the frequency-constrained subspace. The estimated parameters can be utilized for re-simulation, or be altered toward fluid editing. Our novel inverse-modelling technique produces real-time gas sequences after precomputation, and is convenient to couple with other methods for visual enhancement and/or special visual effects. We integrate our new modelling tool with a state-of-the-art fluid capturing approach, forming a complete pipeline from real-world fluid to flow re-simulation and editing for various graphics applications.

References

[1]

{AIH*08} Atcheson B., Ihrke I., Heidrich W., Tevs A., Bradley D., Magnor M., Seidel H.-P.: Time-resolved 3d capture of non-stationary gas flows. ACM Transactions on Graphics Volume 27, Issue 5 2008, pp.132.

Digital Library

[2]

{BJ05} Barbič J., James D. L.: Real-time subspace integration for st.venant-kirchhoff deformable models. ACM Transactions on Graphics Volume 24, Issue 3 2005, pp.982-990.

Digital Library

[3]

{DLJY11} Ding Y., Li F., Ji Y., Yu J.: Dynamic fluid surface acquisition using a camera array. In Proceedings of the IEEE International Conference on Computer Vision ICCV2011, IEEE, pp. pp.2478-2485.

Digital Library

[4]

{DMP05} Damerval C., Meignen S., Perrier V.: A fast algorithm for bidimensional emd. IEEE Signal Processing Letters Volume 12, Issue 10 2005, pp.701-704.

[5]

{DWLF12} <familyNamePrefix>De</familyNamePrefix>Witt T., Lessig C., Fiume E.: Fluid simulation using laplacian eigenfunctions. ACM Transactions on Graphics Volume 31, Issue 1 2012, pp.571-583.

Digital Library

[6]

{Ebe02} Eberly D.: Thin Plate Splines. Geometric Tools Inc ., 2002.

[7]

{ESWVO06} Elsinga G. E., Scarano F., Wieneke B., <familyNamePrefix>Van</familyNamePrefix>Oudheusden B.: Tomographic particle image velocimetry. Experiments in Fluids Volume 41, Issue 6 2006, pp.933-947.

[8]

{FL04} Fattal R., Lischinski D.: Target-driven smoke animation. ACM Transactions on Graphics Volume 23, Issue 3 2004, pp.441-448.

Digital Library

[9]

{FM96} Foster N., Metaxas D.: Realistic animation of liquids. Graphical Models and Image Processing Volume 58, Issue 5 1996, pp.471-483.

Digital Library

[10]

{FM97} Foster N., Metaxas D.: Controlling fluid animation. In Proceedings of the 1997 Conference on Computer Graphics International1997, IEEE Computer Society, pp. pp.178-188.

Digital Library

[11]

{FSJ01} Fedkiw R., Stam J., Jensen H. W.: Visual simulation of smoke. In SIGGRAPH '01: Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques2001, ACM, pp. pp.15-22.

Digital Library

[12]

{FW12} Feng P., Warren J.: Discrete bi-Laplacians and biharmonic B-splines. ACM Transactions on Graphics Volume 31, Issue 4 2012, pp.115:1-115:11.

Digital Library

[13]

{GIT*14} Gregson J., Ihrke I., Thuerey N., Heidrich W.: From capture to simulation-connecting forward and inverse problems in fluids. ACM Transactions on Graphics Volume 33 2014, pp.70-79.

Digital Library

[14]

{GKHH12} Gregson J., Krimerman M., Hullin M. B., Heidrich W.: Stochastic tomography and its applications in 3d imaging of mixing fluids. ACM Transactions on Graphics Volume 31, Issue 4 2012, pp.52:1-52:10.

Digital Library

[15]

{GLRH13} Gao Y., Li C.-F., Ren B., Hu S.-M.: View-dependent multiscale fluid simulation. IEEE Transactions on Visualization and Computer Graphics Volume 19, Issue 2 2013, pp.178-188.

Digital Library

[16]

{HS05} Huang N. E., Shen S. S.: Hilbert-Huang Transform and Its Applications, vol. 5. World Scientific, Singapore, 2005.

[17]

{HSL*98} Huang N. E., Shen Z., Long S. R., Wu M. C., Shih H. H., Zheng Q., Yen N.-C., Tung C. C., Liu H. H.: The empirical mode decomposition and the hilbert spectrum for nonlinear and non-stationary time series analysis. Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences 454, 1971 1998, pp.903-995.

[18]

{JF03} James D. L., Fatahalian K.: Precomputing interactive dynamic deformable scenes. ACM Transactions on Graphics Volume 22, Issue 3 2003, pp.879-887.

Digital Library

[19]

{KD13} Kim T., Delaney J.: Subspace fluid re-simulation. ACM Transactions on Graphics Volume 32, Issue 4 2013, pp.96.

Digital Library

[20]

{KLLR05} Kim B., Liu Y., Llamas I., Rossignac J.: Flowfixer: Using bfecc for fluid simulation. In NPH'05L: Proceedings of the 1st Eurographics Conference on Natural Phenomena2005, Eurographics Association, pp. pp.51-56.

Digital Library

[21]

{Lin09} Linderhed A.: Image empirical mode decomposition: A new tool for image processing. Advances in Adaptive Data Analysis Volume 1, Issue 2 2009, pp.265-294.

[22]

{Lin11} Linderhed A.: Variable sampling of the empirical mode decomposition of two-dimensional signals. International Journal of Wavelets, Multiresolution and Information Processing Volume 3, Issue 3 2011, pp.435-452.

[23]

{LPS*13} Li C., Pickup D., Saunders T., Cosker D., Marshall D., Hall P., Willis P.: Water surface modeling from a single viewpoint video. IEEE Transactions on Visualization and Computer Graphics Volume 19, Issue 7 2013, pp.1242-1251.

Digital Library

[24]

{LS08} Liu T., Shen L.: Fluid flow and optical flow. Journal of Fluid Mechanics Volume 614 2008, pp.253-291.

[25]

{MTPS04} McNamara A., Treuille A., Popović Z., Stam J.: Fluid control using the adjoint method. ACM Transactions on Graphics Volume 23, Issue 3 2004, pp.449-456.

Digital Library

[26]

{NB11} Nielsen M. B., Bridson R.: Guide shapes for high resolution naturalistic liquid simulation. ACM Transactions on Graphics Volume 30, Issue 4 2011, pp.83.

Digital Library

[27]

{NCZ*09} Nielsen M. B., Christensen B. B., Zafar N. B., Roble D., Museth K.: Guiding of smoke animations through variational coupling of simulations at different resolutions. In Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation2009, ACM, pp. pp.217-226.

Digital Library

[28]

{REN*04} Rasmussen N., Enright D., Nguyen D., Marino S., Sumner N., Geiger W., Hoon S., Fedkiw R.: Directable photorealistic liquids. In Proceedings of the 2004 ACM SIGGRAPH/Eurographics Symposium on Computer Animation2004, Eurographics Association, pp. pp.193-202.

Digital Library

[29]

{RLL*13} Ren B., Li C.-F., Lin M. C., Kim T., Hu S.-M.: Flow field modulation. IEEE Transactions on Visualization and Computer Graphics Volume 19, Issue 10 2013, pp.1708-1719.

[30]

{RM10} Rehman N., Mandic D.: Multivariate empirical mode decomposition. Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences Volume 466, Issue 2117 2010, pp.1291-1302.

[31]

{SFK*08} Selle A., Fedkiw R., Kim B., Liu Y., Rossignac J.: An unconditionally stable maccormack method. Journal of Scientific Computing Volume 35 2008, pp.350-371.

Digital Library

[32]

{Sta99} Stam J.: Stable fluids. In SIGGRAPH '99: Proceedings of the 26th Annual Conference on Computer Graphics and Interactive Techniques1999, ACM Press/Addison-Wesley Publishing Co., pp. pp.121-128.

Digital Library

[33]

{SY05} Shi L., Yu Y.: Taming liquids for rapidly changing targets. In Proceedings of the 2005 ACM SIGGRAPH/Eurographics Symposium on Computer Animation2005, ACM, pp. pp.229-236.

Digital Library

[34]

{TKPR09} Thürey N., Keiser R., Pauly M., Rüde U.: Detail-preserving fluid control. Graphical Models Volume 71, Issue 6 2009, pp.221-228.

Digital Library

[35]

{TLP06} Treuille A., Lewis A., Popović Z.: Model reduction for real-time fluids. ACM Transactions on Graphics Volume 25, Issue 3 2006, pp.826-834.

Digital Library

[36]

{TMPS03} Treuille A., McNamara A., Popović Z., Stam J.: Keyframe control of smoke simulations. ACM Transactions on Graphics Volume 22, Issue 3 2003, pp.716-723.

Digital Library

[37]

{WHC11} Wu Z., Huang N. E., Chen X.: The multi-dimensional ensemble empirical mode decomposition method. Advances in Adaptive Data Analysis Volume 1, Issue 3 2011, pp.339-372.

[38]

{WHZQ15} Wang X., Hu J., Zhang D., Qin H.: Efficient emd and Hilbert spectra computation for 3d geometry processing and analysis via space-filling curve. The Visual Computer Volume 31, Issue 6 2015, pp.1135-1141.

Digital Library

[39]

{WLZ*09} Wang H., Liao M., Zhang Q., Yang R., Turk G.: Physically guided liquid surface modeling from videos. ACM Transactions on Graphics TOG Volume 28, Issue 3 2009, pp.90.

Digital Library

[40]

{WST09} Wicke M., Stanton M., Treuille A.: Modular bases for fluid dynamics. ACM Transactions on Graphics Volume 28, Issue 3 2009, pp.341-352.

Digital Library

[41]

{XLLR06} Xu Y., Liu B., Liu J., Riemenschneider S.: Two-dimensional empirical mode decomposition by finite elements. Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences Volume 462, Issue 2074 2006, pp.3081-3096.

[42]

{YCZ11} Yuan Z., Chen F., Zhao Y.: Pattern-guided smoke animation with lagrangian coherent structure. ACM Transactions on Graphics Volume 30, Issue 6 2011, pp.136.

Digital Library

[43]

{YJLY12} Ye J., Ji Y., Li F., Yu J.: Angular domain reconstruction of dynamic 3d fluid surfaces. In Proceedings Of the IEEE Conference on Computer Vision and Pattern Recognition CVPR2012, IEEE, pp. pp.310-317.

Digital Library

[44]

{YKH*09} Yoon J.-C., Kam H. R., Hong J.-M., Kang S. J., Kim C.-H.: Procedural synthesis using vortex particle method for fluid simulation. Computer Graphics Forum Volume 28, Issue ffi7 2009, pp.1853-1859.

[45]

{ZB05} Zhu Y., Bridson R.: Animating sand as a fluid. ACM Transactions on Graphics Volume 24 2005, pp.965-972.

Digital Library

Cited By

Li CQiu SWang CQin H(2021)Learning Physical Parameters and Detail Enhancement for Gaseous Scene Design Based on Data GuidanceIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2020.299121727:10(3867-3880)Online publication date: 1-Oct-2021
https://dl.acm.org/doi/10.1109/TVCG.2020.2991217

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Published In

cover image Computer Graphics Forum

Computer Graphics Forum Volume 36, Issue 6

September 2017

417 pages

ISSN:0167-7055

EISSN:1467-8659

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The Eurographs Association & John Wiley & Sons, Ltd.

Chichester, United Kingdom

Publication History

Published: 01 September 2017

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Cited By

Li CQiu SWang CQin H(2021)Learning Physical Parameters and Detail Enhancement for Gaseous Scene Design Based on Data GuidanceIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2020.299121727:10(3867-3880)Online publication date: 1-Oct-2021
https://dl.acm.org/doi/10.1109/TVCG.2020.2991217

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