Research Papers

Raising Accuracy in Physically Based Simulations Through Scaling Equations

[+] Author and Article Information
Daniel Hofmann

Research Associate
e-mail: daniel.hofmann@iwb.tum.de

Gunther Reinhart

Full Professor for Machine Tools and Production
Technologies at the Technische
Universitaet Muenchen,
Director of the Institute for Machine Tools and
Industrial Management,
Head of the Fraunhofer IWU Department for
Resource-Efficient Converting Machines,
Institute for Machine Tools and Industrial
Management (iwb),
Technische Universität München,
Boltzmannstraße 15,
Garching/Munich 85748, Germany

1Corresponding author.

Contributed by the Design Engineering Division of ASME for publication in the JOURNAL OF COMPUTERS AND INFORMATION DIVISION IN ENGINEERING. Manuscript received October 22, 2012; final manuscript received September 23, 2013; published online October 22, 2013. Editor: Bahram Ravani.

J. Comput. Inf. Sci. Eng 13(4), 041009 (Oct 22, 2013) (5 pages) Paper No: JCISE-12-1193; doi: 10.1115/1.4025590 History: Received October 22, 2012; Revised September 23, 2013; Accepted September 29, 2013

In the recent years, the physically based simulation has been developed and applied to various engineering processes. So far the use of this simulation method was limited to calculate the behavior of objects with large dimensions, as the calculation of small objects leads to severe inaccuracies. Thus, simulation results for small objects cannot be used in the engineering process. However, technical systems often consist of a variety of small functional components and workpieces. This paper proposes a new method to significantly improve the accuracy of physically based simulations of small objects by scaling. First, a set of scaling equations is introduced, which allow physically correct scaling of dynamic rigid body systems. Second, the equations are validated by simulating a cube with an edge length of only 20 μm. In this simulation scenario, the new method is compared to the conventional, nonscaling physically based simulation and the improvements of the simulation results are examined. With the scaling equations, technical systems of small components and workpieces can virtually be tested and optimized. This affects a significant reduction of hardware based time and cost consuming experiments.

Copyright © 2013 by ASME
Your Session has timed out. Please sign back in to continue.


Reinhart, G., and Lacour, F.-F., 2009, “Physically Based Virtual Commissioning of Material Flow Intensive Manufacturing Plants,” 3rd International Conference on Changeable, Agile, Reconfigurable and Virtual Production (CARV 2009), Munich, Germany, Herbert Utz Verlag, Munich, pp. 377–386.
Reinhart, G., and Hofmann, D., 2012, “Physically Based Simulation in Parts Feeding,” Werkstattstechnik Online, 102(6), pp. 435–439.
Berkowitz, D. R., and Canny, J., 1996, “Designing Parts Feeders Using Dynamic Simulation,” Proceedings of the IEEE International Conference on Robotics and Automation (ICRA’96), Minneapolis, MN, IEEE, New York, pp. 1127–1132.
Berkowitz, D. R., and Canny, J., 1997, “A Comparison of Real and Simulated Designs for Vibratory Parts Feeding,” Proceedings of the IEEE International Conference on Robotics and Automation (ICRA’97), Albuquerque, NM, IEEE, New York, pp. 2377–2382.
Zäh, M. F., Spitzweg, M., and Lacour, F.-F., 2008, “Application of a Physical Model for the Simulation of the Material Flow of a Manufacturing Plant,” Inf. Technol., 50(3), pp. 192–198.
Reinhart, G., and Lacour, F.-F., 2011, “Design Metaphors for Physically Based Virtual Commissioning,” 44th CIRP International Conference on Manufacturing Systems (ICMS 2011), Madison, WI, p. 3. Available at: http://conferencing.uwex.edu/conferences/cirp2011/documents/finalprogram.pdf
Eberly, D. H., and Shoemake, K., 2004, “Game Physics,” Morgan Kaufmann Series in Interactive 3D Technology, Elsevier, Morgan Kaufmann Publishers, San Francisco, CA.
Millington, I., 2007, Game Physics Engine Development, Morgan Kaufmann Publishers, San Francisco, CA.
Coumans, E., 2011, “Bullet 2.78 Physics SDK Manual,” p. 7.
Erin, C., 2011, “Box2D v2.2.0 User Manual,” last accessed Feb. 23, 2012. Available at: http://www.box2d.org/manual.html
Ericson, C., 2005, “Real-Time Collision Detection,” Morgan Kaufmann Series in Interactive 3D Technology, Elsevier, Morgan Kaufmann Publishers, San Francisco, CA.
van den Bergen, G., 2004, “Collision Detection in Interactive 3D Environments,” Morgan Kaufmann Series in Interactive 3D Technology, Elsevier, Morgan Kaufmann Publishers, San Francisco, CA.
Baraff, D., 2001, “Physically Based Modeling: Rigid Body Simulation,” 69 p., last accessed Feb. 23, 2012. Available at: http://www.pixar.com/companyinfo/research/pbm2001/pdf/notesg.pdf
Stichlmair, J., 1990, Kennzahlen und Ähnlichkeitsgesetze im Ingenieurwesen, Altos-Verlag, Essen, Germany.
Hofmann, D., Huang, H., and Reinhart, G., 2013, “Automated Shape Optimization of Orienting Devices for Vibratory Bowl Feeders,” ASME J. Manuf. Sci. Eng., 135(5), 8 p. [CrossRef]


Grahic Jump Location
Fig. 1

Inaccuracy of physically based simulation of small objects

Grahic Jump Location
Fig. 2

Dimension matrix (adapted from Ref. [14])

Grahic Jump Location
Fig. 4

Scaled simulation of vibratory bowl feeder and orienting device



Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In