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Issue No.06 - November/December (2010 vol.16)
pp: 1449-1457
Kresimir Matkovic , VRVis Research Center, Vienna, Austria
Denis Gracanin , Virginia Tech
Mario Jelovic , AVL AST Croatia
Andreas Ammer , VRVis Research Center, Vienna, Austria
Alan Lez , VRVis Research Center, Vienna, Austria
Helwig Hauser , University of Bergen, Norway
ABSTRACT
Multiple simulation runs using the same simulation model with different values of control parameters generate a large data set that captures the behavior of the modeled phenomenon. However, there is a conceptual and visual gap between the simulation model behavior and the data set that makes data analysis more difficult. We propose a simulation model view that helps to bridge that gap by visually combining the simulation model description and the generated data. The simulation model view provides a visual outline of the simulation process and the corresponding simulation model. The view is integrated in a Coordinated Multiple Views ;(CMV) system. As the simulation model view provides a limited display space, we use three levels of details. We explored the use of the simulation model view, in close collaboration with a domain expert, to understand and tune an electronic unit injector (EUI). We also developed analysis procedures based on the view. The EUI is mostly used in heavy duty Diesel engines. We were mainly interested in understanding the model and how to tune it for three different operation modes: low emission, low consumption, and high power. Very positive feedback from the domain expert shows that the use of the simulation model view and the corresponding ;analysis procedures within a CMV system represents an effective technique for interactive visual analysis of multiple simulation runs.
INDEX TERMS
visualization in physical sciences and engineering, time series data, coordinated multiple views
CITATION
Kresimir Matkovic, Denis Gracanin, Mario Jelovic, Andreas Ammer, Alan Lez, Helwig Hauser, "Interactive Visual Analysis of Multiple Simulation Runs Using the Simulation Model View: Understanding and Tuning of an Electronic Unit Injector", IEEE Transactions on Visualization & Computer Graphics, vol.16, no. 6, pp. 1449-1457, November/December 2010, doi:10.1109/TVCG.2010.171
REFERENCES
[1] W. Aigner, S. Miksch, W. Muller, H. Schumann, and C. Tominski, Visual methods for analyzing time-oriented data. IEEE Transactions on Visualization and Computer Graphics, 14 (1): 47–60, Jan.-Feb. 2008.
[2] AVL. AVL List GmbH. http://www.avl.com. [last accessed 26 June 2010].
[3] J. Banks, J. S. Carson II, B. L. Nelson, and D. M. Nicol, Discrete-Event System Simulation. Prentice Hall, Upper Saddle River, fifth edition, 2010.
[4] P. Chaufour, G. Millet, S. Neyrat, M. Hedna, and E. Botelle, Advanced modelling of a heavy-truck unit-injector system and its applications in the engine design process. In Proceedings of the Diesel Fuel Injection and Sprays 2004, number 2004-01-0020 in Special Publications Paper Collections. SAE International, Mar. 2004.
[5] H. Doleisch, M. Gasser, and H. Hauser, Interactive feature specification for focus+context visualization of complex simulation data. In G.-P. Bonneau, S. Hahmann, and C. D. Hansen editors Proceedings of the Joint EUROGRAPHICS — IEEE TCVG Symposium on Visualization, pages 239–248. The Eurographics Association, 2003.
[6] G. Greeves, S. Tullis, and B. Barker, Advanced two-actuator EUI and emission reduction for heavy-duty diesel engines. SAE Transactions, 112 (3): 914–931, 2003.
[7] H. Hauser, F. Ledermann, and H. Doleisch, Angular brushing of extended parallel coordinates. In Proceedings of the 2002 IEEE Symposium on Information Visualization (INFOVIS 2002), pages 127–130, 2002.
[8] S. Havre, E. Hetzler, P. Whitney, and L. Nowell, ThemeRiver: Visualizing thematic changes in large documents collections. IEEE Transactions on Visualization and Computer Graphics, 8 (1): 9–20, Jan.-Mar. 2002.
[9] D. F. Jerding and J. T. Stasko, The information mural: A technique for displaying and navigating large information spaces. IEEE Transactions on Visualization and Computer Graphics, 4 (3): 257–271, July-Sept. 1998.
[10] D. A. Keim, Visual exploration of large data sets. Communications of the ACM, 44 (8): 38–44, Aug. 2001.
[11] Z. Konyha, K. Matković, D. Gračanin, M. Jelović, and H. Hauser, Interactive visual analysis of families of function graphs. IEEE Transactions on Visualization and Computer Graphics, 12 (6): 1373–1385, Nov./Dec. 2006.
[12] MathWorks. Simulink — simulation and model-based design. http://www.mathworks.com/products/simulink . [last accessed 26 June 2010].
[13] K. Matković, D. Gračanin, B. Klarin, and H. Hauser, Interactive visual analysis of complex scientific data as families of data surfaces. IEEE Transactions on Visualization and Computer Graphics, 15 (6): 1351–1358, Nov.-Dec. 2009.
[14] K. Matković, H. Hauser, R. Sainitzer, and M. E. Gröller, Process visualization with levels of detail. In Proceedings of the 2002 IEEE Symposium on Information Visualization (INFOVIS 2002), pages 67–70, 2002.
[15] W. Müller and H. Schumann, Visualization for modeling and simulation: Visualization methods for time-dependent data — an overview. In Proceedings of the 35th Conference on Winter Simulation (WSC'03), volume 1, pages 737–745. Winter Simulation Conference, 2003.
[16] P. Pirolli and R. Rao, Table lens as a tool for making sense of data. In Proceedings of the workshop on Advanced Visual Interfaces (AVI'96), pages 67–80, New York, 1996. ACM Press.
[17] T. Tenev and R. Rao, Managing multiple focal levels in table lens. In Proceedings of the IEEE Symposium on Information Visualization 1997, pages 59–63, 122, 1997.
[18] J. J. Thomas and K. A. Cook editors. , Illuminating the path: The Research and Development Agenda for Visual Analytics. IEEE Computer Society, 2005.
[19] J. J. Thomas and K. A. Cook, A visual analytics agenda. IEEE Computer Graphics and Applications, 26 (1): 10–13, Jan./Feb. 2006.
[20] E. R. Tufte, The Visual Display of Quantitative Information. Graphics Press, Cheshire, Connecticut, second edition, 2001.
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