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      Static Optimization of a Compliant Vertical Access Riser

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          The compliant vertical access riser (CVAR) is a new riser concept with good compliance; it can significantly reduce operating costs by eliminating the need for additional machines to operate wells directly on the platform. In this study, we determined the optimal riser parameters in terms of the stress and riser weight by optimizing the CVAR, and we compared the optimization results. A two-dimensional nonlinear static CVAR model was deduced according to the principles of virtual work and variation, and the model was verified using MATLAB. Design of experiments and Kriging method were used to reduce the number of sample calculations and improve the modeling accuracy. An appropriate selection of the multi-objective optimization problem (MOP) and the non-dominated sorting genetic algorithm helped to optimize the CVAR design. The non-dominated sorting genetic algorithm II was used to solve the Pareto frontier of the optimization model in order to provide decision makers with more choices for the optimization results. After optimizing the riser parameters, the geometry of the riser was smoother, and the stress and stress differences were greatly reduced; the maximum equivalent stresses at the top and bottom were reduced by 36.6% and 44%, respectively. In addition, the stress difference in the buoyancy block area was reduced by 20.9%, and the weight of the riser was increased significantly by 28.1%.

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          Author and article information

          Journal of Ocean University of China
          Science Press and Springer (China )
          24 August 2019
          01 October 2019
          : 18
          : 5
          : 1070-1078
          1College of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China
          2Kunming Shipborne Equipment Research and Test Center, China Shipbuilding Industry Corporation, Kunming 650051, China
          Author notes
          *Corresponding author: LOU Min
          Copyright © Ocean University of China, Science Press and Springer-Verlag GmbH Germany 2019.

          The copyright to this article, including any graphic elements therein (e.g. illustrations, charts, moving images), is hereby assigned for good and valuable consideration to the editorial office of Journal of Ocean University of China, Science Press and Springer effective if and when the article is accepted for publication and to the extent assignable if assignability is restricted for by applicable law or regulations (e.g. for U.S. government or crown employees).

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