Korean Journal of Computational Design and Engineering (한국CDE학회논문집)

Society for Computational Design and Engineering (한국CDE학회)
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GPU-accelerated Lattice Boltzmann Simulation for the Prediction of Oil Slick Movement in Ocean Environment

GPU 가속 기술을 이용한 격자 볼츠만법 기반 원유 확산 과정 시뮬레이션

  • Ha, Sol (Engineering Research Institute, Seoul National University) ;
  • Ku, Namkug (Engineering Research Institute, Seoul National University) ;
  • Roh, Myung-Il (Department of Naval Architecture & Ocean Engineering and Research Institute of Marine Systems Engineering, Seoul National University)
  • 하솔 (서울대학교 공학연구소) ;
  • 구남국 (서울대학교 공학연구소) ;
  • 노명일 (서울대학교 조선해양공학과 및 해양시스템공학연구소)
  • Received : 2013.03.27
  • Accepted : 2013.08.21
  • Published : 2013.12.01
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Abstract

This paper describes a new simulation technique for advection-diffusion phenomena over the sea surface using the lattice Boltzmann method (LBM), capable of predicting oil dispersion from tankers. The LBM is used to solve the pollutant transport problem within the framework of the ocean environment. The sea space is represented by the lattices, where each lattice has the information on oil transportation. Since dispersed oils (i.e., oil droplets) at sea are transported by convection due to waves, buoyancy, and turbulent diffusion, the conservation of mass and many physical oil transport rules were used in the prediction model. Since the LBM is modeled using the uniform lattices and simple rules, it can be easily accelerated by the parallel mechanism, for example, GPU-accelerated method. The proposed model using the LBM is used to simulate a simple pollution event with the oil pollutants of 10,000 kL. The simulation results indicate that the LBM method accelerated with the GPU is 6 times faster than that without the GPU.

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References

  1. Inan, A. and Balas, L., 2010, An Application of 2D Oil Spill Model to Mersin Coast, WSEAS Transactions on Environment and Development, 6(5), pp.345-354.
  2. Halil, K., 2007, A Third-order Upwind Scheme for the Advection-diffusion Equation Using Spreadsheets, Advances in Engineering Software, 38(9), pp.688-697. https://doi.org/10.1016/j.advengsoft.2006.10.006
  3. Nakano, T., Kasegawa, J. and Morishita, S., 1998, Coastal Oil Pollution Prediction by a Tanker Using Cellular Automata, OCEANS '98 Conference Proceedings, 3, pp.1324-1328.
  4. Sirakoulis, G., Karafyllidis, I., Thanailakis, A. and Tsalides, P., 2003, A Methodology for Modeling Ecological Systems Based on Cellular Automata, WSEAS Transactions on Computers, 2(4), pp.982-990.
  5. Rusinovic, Z. and Bogunovic, N., 2006, Cellular Automata Based Model for the Prediction of Oil Slicks Behavior, Proceedings of 28th International Conference on Information Technology Interfaces, pp.569-574.
  6. Shyue, S., Chung, J.S., Hong, S.W., Nagata, S., Sarmento, A. and Koterayama, W., 2007, Oil Spill Modeling Using 3D Cellular Automata for Coastal Waters, Proceedings of the International Society of Offshore and Polar Engineers Conference, pp.546-553.
  7. Ha, S., Ku, N.K. and Lee, K.Y., 2011, Battle Space Model Based on Lattice Gas Automata for Underwater Warfare Simulation, Proceedings of Asia Simulation Conference 2011, pp.361-376.
  8. Deng, B., Shi, B.C. and Wang, G.C., 2005, A New Lattice Bhatnagar-Gross-Krook Model for the Convection-diffusion Equation with a Source Term, Chinese Physics Letters, 22(2), pp.267-270. https://doi.org/10.1088/0256-307X/22/2/001
  9. Chopard, B., Falcone, J.L. and Latt, J., 2009, The Lattice Boltzmann Advection-diffusion Model Revisited, The European Physical Journal Special Topics, 171(1), pp.245-249. https://doi.org/10.1140/epjst/e2009-01035-5
  10. Shi, B. and Guo, Z., 2009, Lattice Boltzmann Model for Nonlinear Convection-diffusion Equations, Physical Review E, 79(1), p.016701. https://doi.org/10.1103/PhysRevE.79.016701
  11. Tubbs, K., 2010, Lattice Boltzmann Modeling for Shallow Water Equations Using High Performance Computing, Doctoral Thesis, Louisiana State University.
  12. Zhou, J.G., 2011, Lattice Boltzmann Method for Advection and Anisotropic Dispersion Equation, Journal of Applied Mechanics, 78(2), pp.021007-5. https://doi.org/10.1115/1.4002572
  13. Tubbs, K.R. and Tsai, F.T., 2011, GPU Accelerated Lattice Boltzmann Model for Shallow Water Flow and Mass Transport, International Journal for Numerical Methods in Engineering, 86(3), pp.316-334. https://doi.org/10.1002/nme.3066
  14. Hardy, J., Pomeau, J. and de Pazzis, O., 1973, Time Evolution of a Two-dimensional Classical Lattice System, Physical Review Letters, 31(5), pp.276-279. https://doi.org/10.1103/PhysRevLett.31.276
  15. Frisch, U., Hasslacher, B. and Pomeau, Y., 1986, Lattice-gas Automata for the Navier-Stokes Equation, Physical Review Letters, 56(13), pp.1505-1508. https://doi.org/10.1103/PhysRevLett.56.1505
  16. Bhatnagar, P.L., Gross, E.P. and Krook, M., 1954, A Model for Collision Processes in Gases, Physical Review, 94(3), pp.511-525. https://doi.org/10.1103/PhysRev.94.511
  17. Qian, Y.H., D'Humieres, D. and Lallemand, P., 1992, Lattice BGK Models for Navier-Stokes Equation, Europhysics Letters (EPL), 17(5), pp.479-484. https://doi.org/10.1209/0295-5075/17/6/001
  18. Nguyen, H., 2007, GPU Gems 3: Programming Techniques for High Performance Graphics and General-Purpose Computation, Addison-Wesley Education Publishers, Inc.
  19. Nvidia, C., 2007, Compute Unified Device Architecture Programming Guide, NVIDIA: Santa Clara, CA.