- Michael Kaliske, Institute for Structural Analysis, TU Dresden
- Wolfgang Graf, Institute for Structural Analysis, TU Dresden
- Sigrid Leyendecker, Chair of Applied Dynamics, Friedrich-Alexander-Universität Erlangen-Nürnberg
- Stefanie Reese, Institute for Applied Mechanics, RWTH Aachen
The numerical analysis and design of structures is currently characterised by deterministic thinking and methods. Deterministic modelling of the reality indicates preciseness and safety, while, on contrary, all available data and information are characterized by various types of uncertainty (variability, imprecision, incompleteness), which cannot be neglected.
Engineering solutions are characterized by inherent robustness and flexibility as essential fea-tures for a faultless life of structures and systems under uncertain and changing conditions. An implementation of these features in a structure or system requires a comprehensive consid-eration of uncertainty in the model parameters and environmental and man imposed loads as well as other types of intrinsic and epistemic uncertainties. Numerical design of structures should be robust with respect to (spatial and time dependent) uncertainties inherently present in resistance of materials, boundary conditions etc.
The main focus of this mini-symposium is the presentation of methods for the numerical simu-lation of structures under consideration of data uncertainty. Challenges in this context involve, for example, limited information, human factors, subjectivity and experience, linguistic as-sessments, imprecise measurements, dubious information, unclear physics etc. Due to the pol-ymorphic nature and characteristic of the available infor¬mation both probabilistic and set-theoretical approaches as well as newly developed joint approaches are relevant for solutions.
By the mini-symposium, the opportunities of inter- and transdisciplinary shall be used for the stimulation of synergies between mathematics and engineering sciences. Recent deve¬lop¬ments of numerical methods in the field of engineering design, which include a comprehensive consi-deration of uncertainty and associated efficient analysis techniques, such as advanced Monte Carlo simulations, meta-model approximations, and High Performance Computing strategies are explicitly invited. These may involve imprecise probabilities, interval methods, Fuzzy methods, and further concepts as well as data based uncertainty quantification with suitable uncertainty models as well as multivariate uncertain structural responses and related inverse uncertainty quantification methods for interacting and interdependent uncertain variables.
The contributions may address specific technical or mathematical details, conceptual devel-opments and solution strategies, individual solutions, and may also provide overviews and comparative studies.