TU Dresden, Institute for Structural Analysis, Germany

The challenging task in computational engineering is to model and predict numerically the behavior of engineering structures in a realistic manner. Beside sophisticated numerical procedures to map physical phenomena and processes, an adequate description of available data covering the content of provided information is of prime importance. Generally, the availability of information in engineering practice is limited due to available resources. Far beyond the capability to specify crisp values uncertain data are imprecise, diffuse, fluctuating, incomplete, fragmentary and frequently expert specified.
Beside objective characteristics like randomness, available data are influenced by subjectivity to a considerable extent. This impedes the specification of unique data models with crisp parameter values to describe the data uncertainty. By applying imprecise probabilities, objective components of the uncertainty as well as subjective components can be considered simultaneously. A sophisticated procedure to handle imprecise probabilities provides the uncertainty model, fuzzy randomness. Since fuzziness, randomness, and fuzzy randomness can be processed simultaneously, it is denoted as a generalized uncertainty model.
The developments are demonstrated by means of numerical examples to emphasize their features and by practical, masonry examples to underline their applicability.

Key words
design, reliability, numerical simulation, uncertainty