Structural collapse simulation under consideration of uncertainty - Fundamental concept and results

  • Authors:

  • Dietrich Hartmann;Michael Breidt;van Vinh Nguyen;Friedhelm Stangenberg;Sebastian Höhler;Karl Schweizerhof;Steffen Mattern;Gunther Blankenhorn;Bernd Möller;Martin Liebscher

  • Affiliations:

  • Institute for Computational Engineering, Ruhr-Universität Bochum, 44780 Bochum, Germany;Institute for Computational Engineering, Ruhr-Universität Bochum, 44780 Bochum, Germany;Institute for Computational Engineering, Ruhr-Universität Bochum, 44780 Bochum, Germany;Institute for Reinforced and Prestressed Concrete Structures, Ruhr-Universität Bochum, 44780 Bochum, Germany;Institute for Reinforced and Prestressed Concrete Structures, Ruhr-Universität Bochum, 44780 Bochum, Germany;Institute of Mechanics, Universität Karlsruhe, 76131 Karlsruhe, Germany;Institute of Mechanics, Universität Karlsruhe, 76131 Karlsruhe, Germany;Institute of Mechanics, Universität Karlsruhe, 76131 Karlsruhe, Germany;Institute of Statics and Dynamics of Structures, Dresden University of Technology, 01062 Dresden, Germany;Institute of Statics and Dynamics of Structures, Dresden University of Technology, 01062 Dresden, Germany

  • Venue:
  • Computers and Structures
  • Year:
  • 2008

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Abstract

For the simulation of structural collapse using controlled explosives, the quantification of structural parameters has to be accomplished on the basis of only few data, which may additionally be characterized by vagueness, e.g. due to uncertain measurements or changing reproduction conditions. To ensure a reliable prediction of a structural collapse, next to a close to reality simulation of the complex dynamic process, this uncertainty has to be taken into account. With regard to very high computation associated with the simulation of collapses of real world structures based on conventional finite element models, this paper addresses an efficient approach for the simulation of structural collapse based on multibody models, that simultaneously allow for the investigation of uncertainty.