Blasting of structures
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The local blasting leads to stiffness reductions and structural member
cut off. Physical parameters describing the results of a blasting
process are generally not deterministic thus uncertain. Commonly this
applies for geometric and material parameters. In the stochastic sense
each blasting operation is an individual event that is generally
characterized by limited data and distinctive data uncertainty. For a
formal description of data uncertainty a new mathematical model is
introduced. The uncertainty model fuzzy randomness allows a generalized modeling of uncertainty where the special cases randomness and fuzziness are included. In particular cases the appropriation of the uncertainty model fuzziness may be advisable for some reasons.
The problem is additional characterized by model uncertainty in consequence of varying collapse developments. Model uncertainty acquires the alternative collapse developments as assessed set of simulation models. The structure is subdivided in rigid and flexible parts. During collapse the model represents a multi body system with uncertain material, geometry an load input parameters which are assumed or directly specified. The delayed annihilation of rigid body links yields to the structural collapse with contact, deformation, and fraction situations. The collapse process is identified by system modification e.g. modification of the system geometry, stiffness and system boundary conditions (see Fig. 1)
New analysis algorithms for fuzzified or fuzzy stochastic equations of motion have to be developed due to model and data uncertainty. In case of fuzziness the fuzzy analysis is applied. If uncertainty is interpreted as fuzzy randomness the fuzzy stochastic analysis is deployed. The deterministic fundamental solution a multi body dynamic algorithm is integrated in the described analysis algorithm. As a result of a fuzzy analysis the uncertain maximum debris distance (Fig. 2) is examined. It allows an an assessment of the planed blasting operation with respect to data uncertainty.
The problem is additional characterized by model uncertainty in consequence of varying collapse developments. Model uncertainty acquires the alternative collapse developments as assessed set of simulation models. The structure is subdivided in rigid and flexible parts. During collapse the model represents a multi body system with uncertain material, geometry an load input parameters which are assumed or directly specified. The delayed annihilation of rigid body links yields to the structural collapse with contact, deformation, and fraction situations. The collapse process is identified by system modification e.g. modification of the system geometry, stiffness and system boundary conditions (see Fig. 1)
Fig. 1: Collapsed structure and collapse sequence
New analysis algorithms for fuzzified or fuzzy stochastic equations of motion have to be developed due to model and data uncertainty. In case of fuzziness the fuzzy analysis is applied. If uncertainty is interpreted as fuzzy randomness the fuzzy stochastic analysis is deployed. The deterministic fundamental solution a multi body dynamic algorithm is integrated in the described analysis algorithm. As a result of a fuzzy analysis the uncertain maximum debris distance (Fig. 2) is examined. It allows an an assessment of the planed blasting operation with respect to data uncertainty.
Fig. 2: Fuzzy result - the maximal debris distance
This project - Numerical simulation of blasting
processes under consideration of data and model uncertainty - is part
of the research unit Computer aided destruction of complex structures using controlled explosives (FOR 500) granted by the German Research Foundation (DFG).
References
- Liebscher, M, and Möller, B (2006) Application of the Uncertainty Model Fuzzy Randomness in Multi-Level Simulation of Demolition Processes Using Controlled Explosives, In: NATO Advanced Research Workshop – Extreme Man-Made and Natural Hazards in Dynamics of Structures, edited by Adnan Ibrahimbegovic. NATO-ARW.
- Liebscher, M, Möller, B, and Graf, W (2006) Simulation und Dimensionierung von Abbruchsprengungen, In: Forschungskolloquium Baustatik-Baupraxis. Baustatik -- Baupraxis, Obergurgl.
- Möller, B, and Liebscher, M (2005) Fuzzy multi body systems and fuzzy probabilistic multi body systems and their application for the numerical simulation of controlled demolations od structures, In: Compilation of Abstracts of the Third M.I.T. Conference Computational Fluid and Solid Mechanics, edited by K. J. Bathe. M.I.T., Boston, pages 265.
- Möller, B, Hoffmann, A, and Liebscher, M (2004) Modeling of Blasting Processes in View of Fuzzy Randomness, In: 9th ASCE Specialty Conference on Probabilistic Mechanics and Structural Reliability. ASCE.
© Institute of Statics and Dynamics of Structures (TU Dresden)
