| Summary: | Offshore regions of the Arctic and the Great Lakes hold valuable resources in many respects for harvesting energy and serving as important shipping lanes. Ice loading poses a threat to structures in these regions with high local pressure and various failure modes. It is thus essential to evaluate the ice peak loadings using limited and site-specific data. This thesis aims to better predict the peak ice loading by developing an efficient inverse ice loading prediction methodology and accurate stiffened plate analysis for marine structure design. Additionally, the behavior of the ice-structure interaction is studied mathematically to understand the cyclic dynamic ice-loading applied on offshore structures during continuous ice crushing. Multiple inverse algorithms are presented for calculating the variable ice pressure acting on a stiffened steel plate. The analytical models are formulated to calculate the quasi-static pressure caused by contact of lake ice driven primarily by thermal expansion and winds. Loading pressures are calculated using strain measurements from a stiffened plate installed on a Keweenaw Peninsula lighthouse in Lake Superior. The ice sheet was essentially stationary through the winter months. The linear relationships between pressure and strain values are obtained by both strip beam theory and orthotropic plate theory. The inverse solutions are by nature not necessarily unique. Two inverse approaches using orthotropic plate theory show results with satisfying accuracy and efficiency compared to the finite element analysis. In addition, laboratory calibration and an examination using the recorded data from field measurements exhibit the effectiveness of the presented approach. Continuous ice brittle crushing occurs in the movement of an ice sheet against an offshore structure. Matlock’s ice-structure interaction model is used to simulate the behavior of the ice crushing by modeling ice teeth indentation contacting a spring-mass-dashpot structure. The dynamic behavior of the model is studied ...
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