Skip to main content
SpringerLink
Log in

Interactive 3D simulation for fluid–structure interactions using dual coupled GPUs

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

The scope of this work involves the integration of high-speed parallel computation with interactive, 3D visualization of the lattice-Boltzmann-based immersed boundary method for fluid–structure interaction. An NVIDIA Tesla K40c is used for the computations, while an NVIDIA Quadro K5000 is used for 3D vector field visualization. The simulation can be paused at any time step so that the vector field can be explored. The density and placement of streamlines and glyphs are adjustable by the user, while panning and zooming is controlled by the mouse. The simulation can then be resumed. Unlike most scientific applications in computational fluid dynamics where visualization is performed after the computations, our software allows for real-time visualizations of the flow fields while the computations take place. To the best of our knowledge, such a tool on GPUs for FSI does not exist. Our software can facilitate debugging, enable observation of detailed local fields of flow and deformation while computing, and expedite identification of ‘correct’ parameter combinations in parametric studies for new phenomenon. Therefore, our software is expected to shorten the ‘time to solution’ process and expedite the scientific discoveries via scientific computing.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Similar content being viewed by others

Notes

  1. Lenovo D30, 8 core E5-2609@2.4GHz, 32GB RAM, Windows 7/64.

References

  1. Tian FB, Luo H, Zhu L, Lu XY (2010) Interaction between a flexible filament and a downstream rigid body. Phys Rev E 82:026301

    Article  Google Scholar 

  2. Espinha LC, Hoey DA, Fernandes PR, Rodrigues HC, Jacobs CR (2014) Oscillatory fluid flow influences primary cilia and microtubule mechanics. Cytoskeleton 71:435–445

    Article  Google Scholar 

  3. Huang S, Li R, Li QS (2013) Numerical simulation on fluid–structure interaction of wind around super-tall building at high reynolds number conditions. Struct Eng Mech Int J 46:197–212

    Article  Google Scholar 

  4. Peskin CS (2002) The immersed boundary method. Acta Numer 11:409

    Article  MathSciNet  MATH  Google Scholar 

  5. Mittal R, Iaccarino G (2005) Immersed boundary methods. Annu Rev Fluid Mech 37:239–261

    Article  MathSciNet  MATH  Google Scholar 

  6. LeVeque RJ, Li ZL (1997) Immersed interface methods for Stokes flows with elastic boundaries or surface tension. SIAM J Sci Comput 18:709–735

    Article  MathSciNet  MATH  Google Scholar 

  7. Cortez R (2000) A vortex/impulse method for immersed boundary motion in high Reynolds number flows. J Comput Phys 160:385–400

    Article  MathSciNet  MATH  Google Scholar 

  8. Wang XS (2006) From immersed boundary method to immersed continuum method. Int J Multiscale Comput Eng 4:127–145

    Article  Google Scholar 

  9. Zhang L, Gersternberger A, Wang X, Liu WK (2004) Immersed finite element method. Comput Methods Appl Mech Eng 193:2051

    Article  MathSciNet  MATH  Google Scholar 

  10. Hughes TJR, Liu WK, Zimmermann TK (1981) Lagrangian–Eulerian finite element formulation for incompressible viscous flows. Comput Methods Appl Mech Eng 29:329–349

    Article  MathSciNet  MATH  Google Scholar 

  11. Glowinski R, Pan T, Periaux J (1994) A fictitious domain method for Dirichlet problem and applications. Comput Methods Appl Mech Eng 111:1994

    Article  MathSciNet  MATH  Google Scholar 

  12. Sulsky D, Chen Z, Schreyer HL (1994) A particle method for history-dependent materials. Comput Mech Appl Mech Eng 118:179–197

    Article  MathSciNet  MATH  Google Scholar 

  13. Cottet G-H, Maitre E (2006) A level set method for fluid–structure interactions with immersed surfaces. Math Models Methods Appl Sci 16:415–438

    Article  MathSciNet  MATH  Google Scholar 

  14. Kim J-D, Li Y, Li X (2013) Simulation of parachute FSI using the front tracking method. J Fluids Struct 37:100–119

    Article  Google Scholar 

  15. Peskin CS (1972) Flow patterns around heart valves: a digital computer method for solving the equations of motion, vol 378. PhD thesis. Physiology, Albert Einstein College of Medicine, University of Microfilms, pp 72–30

  16. Peskin CS (1977) Flow patterns around heart valves; a numerical method. J Comput Phys 25:220

    Article  Google Scholar 

  17. McCracken MF, Peskin CS (1980) A vortex method for blood flow through heart valves. J Comput Phys 35:183–205

    Article  MathSciNet  MATH  Google Scholar 

  18. Rosar ME, Peskin CS (2001) Fluid flow in collapsible elastic tubes: a three-dimensional numerical model. New York J Math 7:281–302

    MathSciNet  MATH  Google Scholar 

  19. Roma AM, Peskin CS, Berger MJ (1999) An adaptive version of the immersed boundary method. J Comput Phys 153:509–534

    Article  MathSciNet  MATH  Google Scholar 

  20. Lai MC, Peskin CS (2000) An immersed boundary method with formal second order accuracy and reduced numerical viscosity. J Comput Phys 160:705

    Article  MathSciNet  MATH  Google Scholar 

  21. Griffith BE, Peskin CS (2015) On the order of accuracy of the immersed boundary method: higher order convergence rates for sufficient smooth problems. J Comput Phys 208:75–105

    Article  MATH  Google Scholar 

  22. Zhu L, Peskin CS (2002) Simulation of a flexible flapping filament in a flowing soap film by the immersed boundary method. J Comput Phys 179:452–468

    Article  MathSciNet  MATH  Google Scholar 

  23. Kim Y, Peskin CS (2007) Penalty immersed boundary method for an elastic boundary with mass. Phys Fluids 19:053103

    Article  MATH  Google Scholar 

  24. Fauci LJ, Fogelson AL (1993) Truncated Newton methods and the modeling of complex elastic structures. Commun Pure Appl Math 46:787

    Article  MathSciNet  MATH  Google Scholar 

  25. Taira K, Colonius T (2007) The immersed boundary method: a projection approach. J Comput Phys 225:2118–2137

    Article  MathSciNet  MATH  Google Scholar 

  26. Mori Y, Peskin CS (2008) Implicit second-order immersed boundary method with boundary mass. Comput Methods Appl Mech Eng 197:2049–2067

    Article  MathSciNet  MATH  Google Scholar 

  27. Hao J, Zhu L (2010) A lattice Boltzmann based implicit immersed boundary method for fluid–structure-interaction. Comput Math Appl 59:185–193

    Article  MathSciNet  MATH  Google Scholar 

  28. Hao J, Zhu L (2011) A 3D implicit immersed boundary method with application. Theor Appl Mech Lett 1:062002

    Article  Google Scholar 

  29. Lim S, Ferent A, Wang XS, Peskin CS (2008) Dynamics of a closed rod with twist and bend in fluid. SIAM J Sci Comput 31:273–302

    Article  MathSciNet  MATH  Google Scholar 

  30. Atzberger PJ, Kramer PR, Peskin CS (2006) A stochastic immersed boundary method for biological fluid dynamics at microscopic length scale. J Comput Phys 224:1255–1292

    Article  MATH  Google Scholar 

  31. Zhu L, He G, Wang S, Miller L, Zhang X, You Q, Fang S (2011) An immersed boundary method based on the lattice Boltzmann approach in three dimensions with application. Comput Math Appl 61:3506–3518

    Article  MathSciNet  MATH  Google Scholar 

  32. Feng ZG, Michaelides EE (2005) Proteus: a direct forcing method in the simulations of particulate flows. J Comput Phys 202:20–51

    Article  MATH  Google Scholar 

  33. Tian FB, Luo H, Zhu L, Liao JC, Lu X-T (2011) An efficient immersed boundary-lattice Boltzmann method for the hydrodynamic interaction of elastic filaments. J Comput Phys 230(19):7266–7283

    Article  MathSciNet  MATH  Google Scholar 

  34. Zhang C, Cheng Y, Zhu L, Wu J (2016) Accuracy improvement of the immersed boundary-lattice Boltzmann coupling scheme by iterative force correction. Comput Fluids 124:246–260

    Article  MathSciNet  Google Scholar 

  35. Wu J, Shu C (2009) Implicit velocity correction-based immersed boundary-lattice Boltzmann method and its applications. J Comput Phys 228:1963–1979

    Article  MATH  Google Scholar 

  36. Niu XD, Shu C, Chew YT, Peng Y (2006) A momentum exchange-based immersed boundary-lattice Boltzmann method for simulating incompressible viscous flows. Phys Lett A 354:173–182

    Article  MATH  Google Scholar 

  37. Wu J, Shu C, Zhang YH (2010) Simulation of incompressible viscous flows around moving objects by a variant of immersed boundary-lattice Boltzmann method. Int J Numer Methods Heat Fluid Flow 62:327–354

    MathSciNet  MATH  Google Scholar 

  38. Cheng Y, Zhu L, Zhang C (2014) Numerical study of stability and accuracy of the immersed boundary method coupled to the lattice Boltzmann BGK model. Commun Comput Phys 16:136–168

    Article  MathSciNet  MATH  Google Scholar 

  39. Cheng Y, Zhang H (2010) Immersed boundary method and lattice Boltzmann method coupled FSI simulation of mitral leaflet flow. Comput Fluids 39:871–881

    Article  MathSciNet  MATH  Google Scholar 

  40. Shu C, Liu N, Chew Y-T (2007) A novel immersed boundary velocity correction-lattice Boltzmann method and its application to simulate flow past a circular cylinder. J Comput Phys 226:1607–1622

    Article  MATH  Google Scholar 

  41. Liu N, Peng Y, Liang Y, Lu X (2012) Flow over a traveling wavy foil with a passively flapping flat plate. Phys Rev E 85:056316

    Article  Google Scholar 

  42. Lee P, Griffith BE, Peskin CS (2010) The immersed boundary method for advection–electrodiffusion with implicit timestepping and local mesh refinement. J Comput Phys 229:5208–5227

    Article  MathSciNet  MATH  Google Scholar 

  43. Fai TG, Griffith BE, Mori Y, Peskin CS (2014) Immersed boundary method for variable viscosity and variable density problems using fast constant-coefficient linear solvers II: theory. SIAM J Sci Comput 36:B589–B621

    Article  MathSciNet  MATH  Google Scholar 

  44. Huang H, Sukop M, Lu X (2015) Multiphase lattice Boltzmann methods: theory and application. Wiley, Hoboken

    Book  Google Scholar 

  45. Guo Z, Shu C (2013) Lattice Boltzmann method and its applications in engineering. World Scientific, Singapore

    Book  MATH  Google Scholar 

  46. Qian YH (1990) Lattice gas and lattice kinetic theory applied to the Navier-Stokes equations, PhD thesis. University Pierre et Marie Curie, Paris (1990)

  47. Hou S, Zou Q, Chen S, Doolen G, Cogley A (1995) Simulation of cavity flow by the lattice Boltzmann method. J Comput Phys 118:329

    Article  MATH  Google Scholar 

  48. He X, Chen S, Zhang R (1999) A lattice Boltzmann scheme for incompressible multiphase flow and its application in simulation of Rayleigh-Taylor instability. J Comput Phys 152:642–663

    Article  MathSciNet  MATH  Google Scholar 

  49. Wolf-Gladrow DA (2000) Lattice-gas cellular automata and lattice Boltzmann models—an introduction. Springer, Berlin

    Book  MATH  Google Scholar 

  50. Succi S (2001) The lattice Boltzmann equation. Oxford Univ Press, Oxford

    MATH  Google Scholar 

  51. Luo LS (1998) Unified theory of the lattice Boltzmann models for nonideal gases. Phys Rev Lett 81:1618

    Article  Google Scholar 

  52. Kraus J (2014) Optimizing a LBM code for compute clusters with Kepler GPUs. http://on-demand.gputechconf.com/gtc/2014/presentations/S4186-optimizing-lbm-code-compute-clusters-kepler-gpus.pdf

  53. Valero-Lara P, Igual FD, Prieto-Matías Pinelli A, Favier J (2015) Accelerating fluid–solid simulations (lattice-Boltzmann & immersed-boundary) on heterogeneous architectures. J Comput Sci 10:249–261

    Article  Google Scholar 

  54. Mawson M, Valero-Lara P, Favier J, Pinelli A, Revell A (2013) Fast fluid–structure interaction using lattice Boltzmann and immersed boundary methods. In: NVIDIA GPU Conference

  55. Wu J, Cheng Y, Zhou W, Zhang C, Diao W (2016) GPU acceleration of FSI simulations by the immersed boundary-lattice Boltzmann coupling scheme. Comput Math Appl. doi:10.1016/j.camwa.2016.10.005

  56. Bhaniramka P, Demange Y (2002) OpenGL volumizer: a toolkit for high quality volume rendering of large data sets. In: 2002 Symposium on Volume Visualization and Graphics, pp 45–53

  57. Ahrens J, Geveci B, Law C (2005) ParaView: an end user tool for large data visualization. Visualization Handbook, Elsevier. ISBN 13:978-0123875822

  58. Childs H, Brugger E, Whitlock B, Meredith J, Ahern S, Pugmire D, Biagas K, Miller M, Harrison C, Weber GH, Krishnan H, Fogal T, Sanderson A, Garth C, Bethel E, Camp D, Rübel O, Durant M, Favre JM, Navrátil P (2012) VisIt: an end-user tool for visualizing and analyzing very large data. In: High performance visualization—enabling extreme-scale scientific insight, pp 357–372

  59. Bhatnagar PL, Gross EP, Krook M (1954) A model for collision processes in gases, I; small amplitude process in charged and neutral one-component system. Phys Rev 94:511

    Article  MATH  Google Scholar 

  60. Bailey M, Cunningham S (2012) Graphics shaders theory and practice, 2nd edn. CRC Press, Boca Raton

    Google Scholar 

  61. Weiskopf D (2006) GPU based interactive visualization techniques. Springer, Berlin

    MATH  Google Scholar 

  62. Telea AC (2015) Data visualization principles and practice, 2nd edn. CRC Press, Boca Raton

    Google Scholar 

  63. Yu H, Wang C, Ma KL (2007) Parallel hierarchical visualization of large time-varying 3D vector fields. In: Proceedings of the 2007 ACM/IEEE conference on Supercomputing, ACM, Nov 16, p 24

  64. Xu C, Prince J (1998) Snakes, shapes, and gradient vector flow. IEEE Trans Image Process 7:359–369

    Article  MathSciNet  MATH  Google Scholar 

  65. Spencer B, Laramee RS, Chen G, Zhang E (2009) Evenly space streamlines for surfaces: an image based approach. Comput Graph Forum 28:1618–1631

    Article  Google Scholar 

  66. Max N, Becker B, Crawfis R (1993) Flow volumes for interactive vector field visualization. In: Proceedings Visualization ’93, pp 19–24

Download references

Acknowledgements

The authors would like to thank the NSF support under the Grant award Number DMS-1522554.

Author information

Authors and Affiliations

  1. Beckman Coulter, Indianapolis, IN, 46268, USA

    Bob Zigon

  2. Department of Mathematical Sciences, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202, USA

    Luoding Zhu

  3. Department of Computer Science, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202, USA

    Fengguang Song

Authors
  1. Bob Zigon
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Luoding Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Fengguang Song
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bob Zigon.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zigon, B., Zhu, L. & Song, F. Interactive 3D simulation for fluid–structure interactions using dual coupled GPUs. J Supercomput 74, 37–64 (2018). https://doi.org/10.1007/s11227-017-2103-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-017-2103-x

Keywords

Search

Navigation