Fuzzy-stochastic methods for polymorphic uncertainty modeling of lightweight structures

The overall aim of the research project is to transfer the polymorphic uncertainty models developed in the first funding period into the life cycle of hybrid lightweight structures. In particular, the manufacturing as well as the subsequent use during service time of fiber reinforced plastics (FRPs) in hybrid systems are investigated. During the manufacturing process curing of the matrix is a dominant effect as it is highly temperature dependent and influences strongly the mechanical, thermal and chemical properties of FRPs. During the service time damage and failure are dominant effects, resulting e.g. from repeated loading or crash. The modeling of both, the manufacturing process and the subsequent use during service time can be done on different scales. The entire modeling from manufacturing to service time is implemented using a three-scale model that takes into account curing and damage combined to polymorphic uncertainty. This model is applied to determine effective properties from one scale to the next higher. Uncertainties are quantified from already existing experimental data.

Suitable fuzzy-stochastic homogenization methods determine the polymorphic uncertain effective properties of the matrix after curing. In combination with the properties of the fibers macro scale effective parameters are obtained for the composite by suitable fuzzy-stochastic homogenization methods. These effective parameters are compared with existing experimental data of the composite. In order to investigate not only the uncertainty of the composite, additional biaxial tests will be performed in order to investigate dependencies of individual parameters of the composite.

In order to adequately represent real loading conditions during the service time, uncertain failure mechanisms by use of homogenization methods are taken into account. As a starting point, existing heterogeneous data will be used to quantify uncertainty in damage parameters. In order to consider complex structures for the validation of the model, the developed fuzzy-stoschastic methods are extended to a finite element formulation. For comparison already existing experimental results are used for a top hat profile.