Visualization of Results Received with the Discrete Element Method
Kostek Robert 1, Munjiza Antonio 2
University of Technology and Life Sciences, Faculty of Mechanical Engineering
al. Prof. S. Kaliskiego 7, 85-796 Bydgoszcz, Poland
e-mail robertkostek@o2.pl
Queen Mary, University of London, Department of Engineering, 328D
Mile End Road, London, UK, E1 4NS
e-mail: a.munjiza@qmul.ac.uk
Website: http://webspace.qmul.ac.uk/amunjiza
Received:
Received: 03 May 2009; revised: 22 September 2009; accepted: 02 October 2009; published online: 26 November 2009
DOI: 10.12921/cmst.2009.15.02.151-160
OAI: oai:lib.psnc.pl:670
Abstract:
The output of discrete element simulations includes thousands of time-frames and millions of interacting particles (bodies) in each frame. A single simulation can include terabytes of results, which may lead to very large, very complex data sets. Visualizing them is coupled with difficulties caused by either the number of particles, the number of time-frames or complexities of “system variables”. In this work, an attempt has been made to present a data format and graphical template dedicated to discrete element visualization. The article presents a practical approach to the issues, that is the result of programming an open source 3D visualizer, called DEV_KM.
Key words:
References:
[1] R. Kostek, Simulation of the granular flow within an impact crusher. Inżynieria i Aparatura Chemiczna 48(2), 74-75 (2009).
[2] J.P. Latham, A. Munjiza, X. Garcia, J. Xiang and R. Guises, Three-dimensional particle shape acquisition and use of shape library for DEM and FEM/DEM simulation. Minerals Engineering 21(11) (2008).
[3] T. Tsuji, K. Yabumoto and T. Tanaka, Spontaneous structures in three-dimensional bubbling gas-fluidized bed by parallel DEM–CFD coupling simulation. Powder Technology 184(2), 132-140 (2008).
[4] ParaView, http://www.paraview.org
[5] Wm. G. Hoover, Computational Physics with Particles – Nonequilibrium Molecular Dynamics and Smooth Particle Applied Mechanic. Computational Methods in Science and Technology 13(2), 83-93 (2007).
[6] F.Y. Fraige, P.A. Langston and G.Z. Chen, Distinct element modelling of cubic particle packing and flow. Powder Technology 186(3) 224-240 (2008).
[7] W.R. Ketterhagen, J.S. Curtis, C.R.Wassgren and B.C. Hancock, Modeling granular segregation in flow from quasithree-dimensional, wedge-shaped hoppers. Powder Technology 179(3), 126-143 (2008).
[8] The Scientific Computing and Imaging (SCI) Institute web site http://www.sci.utah.edu
[9] C.P. Gribble, C. Brownlee and S.G. Parker, Practical global illumination for interactive particle visualization. Computers & Graphics 32(1), 14-24 (2008).
[10] M.L. Sawley, J. Biddiscombe and J.M. Favre, Advanced visualization of large datasets for discrete element method simulations. Discrete Element Methods (DEM) ’07, Brisbane, Australia, 26-29 August 2007.
[11] S. Weyna, Microflown based identication of vortex shadding in the space of real acoustic flow fields. The Twelfth International Congresson Sound and Vibration, CSV12, Lisbon, Portugal, 690, 2005.
[12] S. Weyna, Image of acoustic energy field radiated in 3d space by electrodynamic loudspeaker. 19th International Congress on Acoustics Madrid, 2007.
[13] M. Hlawitschka and G. Scheuermann, HOT Lines: Tracking lines in higher order tensor fields. 16-th IEEE Visualization (VIS 2005), 27-34 (2005).
[14] M. Schirski, T. Kuhlena, M. Hoppb, P. Adomeit, S. Pischinger and C. Bischof, Virtual Tubelets – efficiently visualizing large amounts of particle trajectories. Computers & Graphics, 29(1) 17-27 (2005).
[15] F. Goes, S. Goldensteina and L. Velhob, A simple and flexible framework to adapt dynamic meshes. Computers & Graphics 32(2) 141-148 (2008).
[16] Y. Xi and Y. Duan, A novel region-growing based isosurface extraction algorithm. Computers & Graphics, doi: 10.1016/ j.cag. 2008.09.007.
[17] A. Wiebel, C. Garth and G. Scheuermann, Computation of localized flow for steady and unsteady vector fields and its applications. IEEE Trans. Visualization and Computer Graphics 1(8) (2002).
[18] P.W. Cleary and J. Ha, Three-dimensional SPH simulation of light metal components. J. Light Metals 2(3), 16-183 (1993).
[19] P.W. Cleary and J. Ha, Modelling the high pressure die casting process using SPH. Material Forum 25, 1-29 (2001).
[20] Visualization Toolkit (VTK), http://www.vtk.org
[21] Rheingans P., Task-based color scale design. Proceedings of Applied Image and Pattern Recognition ’99, SPIE, 35-43 (1999).
The output of discrete element simulations includes thousands of time-frames and millions of interacting particles (bodies) in each frame. A single simulation can include terabytes of results, which may lead to very large, very complex data sets. Visualizing them is coupled with difficulties caused by either the number of particles, the number of time-frames or complexities of “system variables”. In this work, an attempt has been made to present a data format and graphical template dedicated to discrete element visualization. The article presents a practical approach to the issues, that is the result of programming an open source 3D visualizer, called DEV_KM.
Key words:
References:
[1] R. Kostek, Simulation of the granular flow within an impact crusher. Inżynieria i Aparatura Chemiczna 48(2), 74-75 (2009).
[2] J.P. Latham, A. Munjiza, X. Garcia, J. Xiang and R. Guises, Three-dimensional particle shape acquisition and use of shape library for DEM and FEM/DEM simulation. Minerals Engineering 21(11) (2008).
[3] T. Tsuji, K. Yabumoto and T. Tanaka, Spontaneous structures in three-dimensional bubbling gas-fluidized bed by parallel DEM–CFD coupling simulation. Powder Technology 184(2), 132-140 (2008).
[4] ParaView, http://www.paraview.org
[5] Wm. G. Hoover, Computational Physics with Particles – Nonequilibrium Molecular Dynamics and Smooth Particle Applied Mechanic. Computational Methods in Science and Technology 13(2), 83-93 (2007).
[6] F.Y. Fraige, P.A. Langston and G.Z. Chen, Distinct element modelling of cubic particle packing and flow. Powder Technology 186(3) 224-240 (2008).
[7] W.R. Ketterhagen, J.S. Curtis, C.R.Wassgren and B.C. Hancock, Modeling granular segregation in flow from quasithree-dimensional, wedge-shaped hoppers. Powder Technology 179(3), 126-143 (2008).
[8] The Scientific Computing and Imaging (SCI) Institute web site http://www.sci.utah.edu
[9] C.P. Gribble, C. Brownlee and S.G. Parker, Practical global illumination for interactive particle visualization. Computers & Graphics 32(1), 14-24 (2008).
[10] M.L. Sawley, J. Biddiscombe and J.M. Favre, Advanced visualization of large datasets for discrete element method simulations. Discrete Element Methods (DEM) ’07, Brisbane, Australia, 26-29 August 2007.
[11] S. Weyna, Microflown based identication of vortex shadding in the space of real acoustic flow fields. The Twelfth International Congresson Sound and Vibration, CSV12, Lisbon, Portugal, 690, 2005.
[12] S. Weyna, Image of acoustic energy field radiated in 3d space by electrodynamic loudspeaker. 19th International Congress on Acoustics Madrid, 2007.
[13] M. Hlawitschka and G. Scheuermann, HOT Lines: Tracking lines in higher order tensor fields. 16-th IEEE Visualization (VIS 2005), 27-34 (2005).
[14] M. Schirski, T. Kuhlena, M. Hoppb, P. Adomeit, S. Pischinger and C. Bischof, Virtual Tubelets – efficiently visualizing large amounts of particle trajectories. Computers & Graphics, 29(1) 17-27 (2005).
[15] F. Goes, S. Goldensteina and L. Velhob, A simple and flexible framework to adapt dynamic meshes. Computers & Graphics 32(2) 141-148 (2008).
[16] Y. Xi and Y. Duan, A novel region-growing based isosurface extraction algorithm. Computers & Graphics, doi: 10.1016/ j.cag. 2008.09.007.
[17] A. Wiebel, C. Garth and G. Scheuermann, Computation of localized flow for steady and unsteady vector fields and its applications. IEEE Trans. Visualization and Computer Graphics 1(8) (2002).
[18] P.W. Cleary and J. Ha, Three-dimensional SPH simulation of light metal components. J. Light Metals 2(3), 16-183 (1993).
[19] P.W. Cleary and J. Ha, Modelling the high pressure die casting process using SPH. Material Forum 25, 1-29 (2001).
[20] Visualization Toolkit (VTK), http://www.vtk.org
[21] Rheingans P., Task-based color scale design. Proceedings of Applied Image and Pattern Recognition ’99, SPIE, 35-43 (1999).
