Search

Apart from the mechanisms of ice structure interactions under various scenarios of sea ice conditions and structural configurations, the selection of probabilistic models is crucial in order to cope with the loading uncertainty. Sea ice is the primary contributor to design loads in cold regions. In many cases, ice loads present the highest magnitude. In recent years, the probabilistic study of ice thickness, ice strength coefficient, flexural strength, ice drift speed, etc., has significantly increased, corresponding to the increasing activity of offshore operations in cold regions as well as the development of instrument technology for sea ice observation. This paper reviews existing probabilistic modes of sea ice, which are used to estimate the uncertainty of ice loading with various types of offshore structures, including vertical structures, sloping structures, and stations with floating vessels. The ISO 19906 standard is employed for the probabilistic assessment of vertical and sloping structures. The interactions between ice and structures on sloping structures are considered in both the upward and downward directions. The ice resistance method is applied for station-keeping floating vessels in ice. The key parameters of sea ice properties to estimate the design loads are studied. The effect of correlation between the key parameters of ice loads is investigated. This review shows that most existing probabilistic models are proposed for the estimation of ice loading on the various types of offshore structures. [ABSTRACT FROM AUTHOR]

Offshore jacket platforms are widely used for oil and gas extraction as well as transportation in shallow to moderate water depth. Tubular cross‐sectional elements are used to construct offshore platforms. Tubular cross sections impart higher resistance against hydrodynamic forces and have high torsional rigidity. During operation, the members can be partially or fully damaged due to lateral impacts. The lateral impacts can be due to ship collisions or through the impact of falling objects. The impact forces can weaken some members that influence the overall performance of the platform. This demonstrates an urgent need to develop a framework that can accurately forecast dent depth as well as dent angle of the affected members. This study investigates the use of an adaptive metaheuristics algorithm to provide automatic detection of denting damage in an offshore structure. The damage information includes dent depth and the dent angle. A model is developed in combination with the percentage of the dent depth of the damaged member and is used to assess the performance of the method. It demonstrates that small changes in stiffness of individual damaged bracing members are detectable from measurements of global structural motion. [ABSTRACT FROM AUTHOR]