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Centrifuge modelling of the monotonic capacity of ...
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The study used 70g centrifuge tests to investigate the monotonic tensile capacity of offshore ring anchors embedded in sand. Ring anchors may reduce foundation material and transport costs compared with suction caissons or monopiles, while allowing deeper installation than drag-embedment anchors.<br /><br />Tests were conducted in dense, dry Ottawa F65 sand prepared by pluviation. Researchers measured force–displacement behavior and developed load-interaction diagrams for two embedment depths and four load inclinations. The tests also examined installation-related soil disturbance.<br /><br />Anchor tensile capacity increased with greater embedment and with a more vertical load direction. The force–displacement response had a steep initial slope followed by a more gradual increase; capacity generally rose with displacement, with a slight decrease under vertical pulling. Failure involved different mechanisms depending on embedment and load direction, including cone-shaped failure and deeper flow-around mechanisms. These mechanisms affect both capacity and system stiffness.<br /><br />Initial numerical predictions matched the shallow-anchor results but overestimated the deep anchor’s vertical capacity. After accounting for installation disturbance, updated numerical results matched both shallow and deep test results more closely. The findings indicate that installation effects should be considered in design.<br /><br />Future work includes monotonic tests in clay, including measurements of pore-pressure changes, and cyclic testing under representative environmental load histories. Researchers also plan to assess multiline anchor arrangements, where load sharing may reduce the number of anchors or individual anchor loads but introduces more complex, potentially reversing and multidirectional loading.
Keywords
offshore ring anchors
centrifuge tests
tensile capacity
embedment depth
load inclination
Ottawa F65 sand
force-displacement behavior
soil disturbance
failure mechanisms
numerical prediction
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