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Item type:Publication, Access status: without files , The non-linear behavior of aqueous model ice in downward flexureAs aqueous model ice is used extensively in ice tanks tests on the performance of ship hulls in sheet ice, it is imperative that such model ice replicate the main flexural strength behavior of sheets of sea ice and freshwater ice. Ice tanks use various types of aqueous model ice types, each of which contain brine dopants to scale-reduce ice-sheet strength. Dopants, though, introduce non-linear trends in the scaled flexural behavior of model ice sheets, and can affect ice loads and ice-rubble at ship-hulls and structures. This paper analyzes the non-linear behavior of model ice, and shows that all types behave non-linearly in flexure independent from crystal structure or chemical dopant. Such behavior is attributable to plasticity and vertical variations in stiffness and strength through sheets of model ice. Additionally, the problematic formation of a top layer in model ice sheets is shown to have a greater impact of sheet behavior than the literature reports heretofore. There remains a significant knowledge gap regarding the freezing and movement of brine dopants within ice sheets and their impact on the non-linear behavior. Additionally, it is found that the Hertz method for estimating the Cauchy number of model ice does not reflect the actual deformation behavior of model ice and should be revised.Publicationtype: Journal Article279 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Establishing a common database of ice experiments and using machine learning to understand and predict ice behaviorIce material models often limit the accuracy of ice related simulations. The reasons for this are manifold, e.g. complex ice properties. One issue is linking experimental data to ice material modeling, where the aim is to identify patterns in the data that can be used by the models. However, numerous parameters that influence ice behavior lead to large, high dimensional data sets which are often fragmented. Handling the data manually becomes impractical. Machine learning and statistical tools are applied to identify how parameters, such as temperature, influence peak stress and ice behavior. To enable the analysis, a common and small scale experimental database is established.Publicationtype: Journal Article290 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , State of the art and knowledge gaps on modelling structures in cold regions(American Society of Mechanical Engineers (ASME), 2019-06); ; ; ; The environment in cold regions undergoes significant changes that manifest in rising temperatures and melting ice caps. These processes allow access to new areas for shipping and the installation of structures. However, the occurring changes are not solely a reduction of ice, but also waves increasingly occur in cold regions contributing to ice break up in the Marginal Ice Zone (MIZ) and the transport of ice towards the open sea. Much work has been done to combine the single topic disciplines: wave-hydrodynamics, ice mechanics and structure mechanics to wave-structure (WSI) and ice-structure interaction (ISI). The changing environment in cold regions and the increased wave activity form a new combined discipline: wave-ice-structure interaction (WISI). This paper addresses existing knowledge gaps of the future loading scenario WISI that need to be addressed in engineering to ensure safety for future operations in Polar Regions. The knowledge gaps however, do not only refer to the discipline interfaces, i.e. challenges in combining them, but also to knowledge gaps within them. Wave statistics and the cross-effect between wave and ice are widely unknown which limits the definition of a design wavescenario. Structures in such environments are exposed to subzero temperatures and neither their impact on properties nor on fatigue life is fully understood. While most phenomena of these two disciplines and their implementation into numerical models are established the ice mechanics appear as the weakest link. Ice is a complex material and not all aspects of its mechanical behaviour are understood and if - the implementation into (numerical) models has not been successful yet. Ice pieces that are energetically charged by waves and collide with structures at high velocities and for such high impact loads the governing ice mechanics are hardly covered by the state of the art or not at all.Publicationtype: Conference Paper257 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , 202 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A cohesive model for ice and its verification with tensile splitting testsPublicationtype: Conference Paper66 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Review of ice load standards and comparison with measurements(American Society of Mechanical Engineers (ASME), 2017-06); ; Sea ice can interact with offshore structures in regions with at least seasonal ice coverage. Therefore the prediction of ice loads on offshore structures is required by many standards or classification rules and guidelines. In order to do this, empirical formulas are often prescribed. These are based on assumptions in combination with model or full scale tests. Yet there are very few publications where the results of the formulas are actually compared to measurements. A case study is made for ice loads on the Norströmsgrund lighthouse. First of all current empirical formulas given by standards bodies or classification societies are reviewed with focus on applicability. Secondly, the ice loads predicted by the empirical formulas are compared to measurements. It was found that for the given case most methods significantly overestimate the load. The applicability of some methods is disputable.Publicationtype: Conference Paper110