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Bernd Möller, Michael Beer, and Martin Liebscher (2005)
Fuzzy analysis as alternative to stochastic methods - theoretical aspects
In: Proceedings of the 4th German LS-DYNA Forum 2005. DYNAmore, Bamberg, pages D-I-29 -- D-I-43.
A realistic and reliable numerical simulation demands suitable computational models and applicable
data models for the structural design parameters. Structural design parameters are in general nondeterministic,
i.e. uncertain. The choice of an appropriate uncertainty model for describing selected
structural design parameters depends on the characteristic of the available information. Besides the
most often used probabilistic models and the related stochastic analysis techniques newer uncertainty
models offer the chance taking account of non-stochastic uncertainty that frequently appears in engineering
problems.
The uncertainty model fuzziness and the algorithm of the fuzzy structural analysis is presented in this
paper. The uncertainty quantification of real-world data for the uncertainty models fuzziness and randomness
is discussed by the way of examples. The differences and advantages of uncertainty models
randomness and fuzziness and its simulation techniques are addressed.
