Advertisement

Analysis of Granular Chute Flow Based on a Particle Model Including Uncertainties

  • F. Fleissner
  • T. Haag
  • M. Hanss
  • P. Eberhard
Part of the Lecture Notes in Applied and Computational Mechanics book series (LNACM, volume 58)

Abstract

In alpine regions human settlements and infrastructure are at risk to be hit by landslides or other types of geological flows. This paper presents a new approach that can aid the design of protective constructions. An uncertainty analysis of the flow around a debris barrier is carried out using a chute flow laboratory model of the actual debris flow. A series of discrete element simulations thereby serves to assess barrier designs. In this study, the transformation method of fuzzy arithmetic is used to investigate the influence of epistemically uncertain model parameters. It turns out that parameter and modeling uncertainties can have a tremendous influence on the predicted efficiency of protective structures.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bourrier, F., Dorren, L., Nicot, F., Berger, F., Darve, F.: Toward objective rockfall trajectory simulation using a stochastic impact model. Geomorphology 110, 68–79 (2009)CrossRefGoogle Scholar
  2. 2.
    Brendel, L., Dippel, S.: Lasting contacts in molecular dynamics simulations. In: Herrmann, H.J., Hovi, J.-P., Luding, S. (eds.) Physics of Dry Granular Materials. NATO ASI Series E, pp. 313–318. Kluwer Academic Publishers, Dordrecht (1998)Google Scholar
  3. 3.
    Chao-Lung, T., Jyr-Ching, H., Ming-Lang, L., Lacques, A., Chia-Yu, L., Yu-Chang, C., Hao-Tsu, C.: The Tsaoling landslide triggered by the Chi-Chi earthquake, Taiwan: Insights from a discrete element simulation. Engineering Geology 106, 1–19 (2009)CrossRefGoogle Scholar
  4. 4.
    Cundall, P.A.: A computer model for simulating progressive, large-scale movements in blocky rock systems. In: Proceedings of the Symposium of the International Society of Rock Mechanics, Nancy (1971)Google Scholar
  5. 5.
    Cundall, P.A., Strack, O.D.L.: A discrete numerical model for granular assemblies. Géotechnique 29, 47–56 (1979)CrossRefGoogle Scholar
  6. 6.
    Easterbrook, D.J.: Surface Processes and Landforms, 2nd edn. Prentice-Hall, Upper Saddle River (1999)Google Scholar
  7. 7.
    Fleissner, F.: Parallel Object Oriented Simulation with Lagrangian Particle Methods. In: Schriften aus dem Institut für Technische und Numerische Mechanik der Universität Stuttgart, Shaker Verlag, Aachen (2010)Google Scholar
  8. 8.
    Fleissner, F., Eberhard, P.: Examples for modeling, simulation and visualization with the discrete element method in mechanical engineering. In: Talaba, D., Amditis, A. (eds.) Product Engineering: Tools and Methods Based on Virtual Reality, pp. 419–426. Springer, Heidelberg (2008)Google Scholar
  9. 9.
    Fleissner, F., Gaugele, T., Eberhard, P.: Applications of the discrete element method in mechanical engineering. Multibody System Dynamics 18(1), 81–94 (2007)zbMATHCrossRefMathSciNetGoogle Scholar
  10. 10.
    Gauger, U., Turrin, S., Hanss, M., Gaul, L.: A new uncertainty analysis for the transformation method. Fuzzy Sets and Systems 159, 1273–1291 (2007)CrossRefMathSciNetGoogle Scholar
  11. 11.
    Hanss, M.: The transformation method for the simulation and analysis of systems with uncertain parameters. Fuzzy Sets and Systems 130(3), 277–289 (2002)zbMATHCrossRefMathSciNetGoogle Scholar
  12. 12.
    Hanss, M.: The extended transformation method for the simulation and analysis of fuzzy-parameterized models. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 11(6), 711–727 (2003)zbMATHCrossRefMathSciNetGoogle Scholar
  13. 13.
    Hanss, M.: Applied Fuzzy Arithmetic – An Introduction with Engineering Applications. Springer, Berlin (2005)zbMATHGoogle Scholar
  14. 14.
    Hanss, M., Herrmann, J., Haag, T.: Vibration analysis of fluid-filled piping systems with epistemic uncertainties. In: Proceedings of the IUTAM Symposium on the Vibration Analysis of Structures with Uncertainties. St. Petersburg, Russia (2009)Google Scholar
  15. 15.
    Hofer, E.: When to separate uncertainty and when not to separate. Reliability Engineering and System Safety 54(2-3), 113–118 (1996)CrossRefGoogle Scholar
  16. 16.
    Hsü, K.J.: Catastrophic debris streams (sturzstroms) generated by rockfalls. Geological Society of America Bulletin 86, 129–140 (1975)CrossRefGoogle Scholar
  17. 17.
    Kaufmann, A., Gupta, M.M.: Introduction to Fuzzy Arithmetic. Van Nostrand Reinhold, New York (1991)zbMATHGoogle Scholar
  18. 18.
    Loeven, G.J.A., Bijl, H.: Probabilistic collocation used in a two-step approach for efficient uncertainty quantification in computational fluid dynamics. CMES – Computer Modeling in Engineering & Sciences 36(3), 193–212 (2008)MathSciNetGoogle Scholar
  19. 19.
    Proske, D., Kaitna, R., Suda, J., Hübl, J.: Abschätzung einer Anprallkraft für murenexponierte Massivbauwerke. Bautechnik 85(12), 803–811 (2008)CrossRefGoogle Scholar
  20. 20.
    Jefferson Stroud, W., Krishnamurthy, T., Smith, S.A.: Probabilistic and possibilistic analyses of the strength of bonded joint. CMES – Computer Modeling in Engineering & Sciences 3(6), 755–772 (2002)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • F. Fleissner
    • 1
  • T. Haag
    • 2
  • M. Hanss
    • 2
  • P. Eberhard
    • 1
  1. 1.Institute of Engineering and Computational MechanicsUniversity of StuttgartStuttgartGermany
  2. 2.Institute of Applied and Experimental MechanicsUniversity of StuttgartStuttgartGermany

Personalised recommendations