Flexible risers connect offshore platforms with subsea production systems.Lazy wave configurations can alleviate top tension and fatigue damage.The tether in the riser touch down area plays an important role in fixed subsea risers.However,designing lazy wave riser systems with added anchor chains is more complex.Through basic theory calculations of lazy-wave type principles,a reasonable initial riser state is determined.Subsequently,utilizing the OrcaFlex riser analysis software and considering environmental factors,vessel structure,riser materials,line types,gravity blocks,buoyancy blocks,anchor chains,and other configuration parameters,a finite element model of the lazy wave riser system is established.Static and dynamic analyses validate compliance with five predetermined constraints regarding riser configuration,tension,bending radius,anchor chain tension,and FPSO offset.Combining neural network optimization algorithms and genetic algorithms,an optimization algorithm tailored to the riser system is devised.MATLAB programming minimizes the number of buoyancy blocks.Then,based on the L-M algorithm,a neural network model is constructed,enhancing precision through iterative training to obtain the final parameter optimization results.Comparison of static and dynamic analysis results before and after optimization reveals a significant reduction in the number of buoyancy blocks and a substantial decrease in maximum effective tension in the riser.However,the depth of the lowest point in the suspended section increases to some extent,indicating a more reasonable lazy wave configuration overall.
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