Development of a multi scale ice material model for the simulation of brittle ice structure interaction

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Ice covered sea areas have become attractive for various stakeholders. This includes e.g. oil and gas, navy and fishing. At the same time it is known that sea ice can cause significant damage. Hence the need for reliable ice load design methods for ships and offshore structures operating in these areas has increased. At present, this is mostly done with empirical methods or model scale ice tests. Both methods come with drawbacks. Empirical methods fail to predict ice-induced loading with sufficient accuracy and only give global ice loads. Mode scale ice tests are linked to controversial topics such as scaling laws or ways of making artificially weakened ice.In this regard, numerical simulations of ice interaction are a desirable tool. Simulations include additional aspects in the design process such as local loads or deformable structures which are not covered by current methods. However, the accuracy of simulations is limited by available ice material models, which only partially capture complex ice behavior. This research aims to identify dominant features of brittle ice structure interaction (ISI) with regard to ice loads. A multi-scale ice material model is to be developed which reflects these dominant features. The key concepts are the use of sub models, where every sub model reflects another aspect of ISI, and scalability, i.e. applicability of the material model to different scales. Three sub models will be used, one will reflect the bulk behavior of ice, e.g. elasticity, a fracture model will reflect multiple macro fractures and finally a stochastic model for the variation of material properties. Further, each sub model will be verified with a broad range of experiments on different scales. Ultimately, the complete material model will be verified against a large scale laboratory experiment. A series of well documented benchmark experiments will be established for comparison and verification of ice material models from other researchers. Additionally, an existing large data experimental data base will be used and extended within this project. Both the benchmarks and the data base will be made available to the public.Presuming success, a future transfer to full scale applications with saline ice is within reach.