Tie-in spools must be designed to resist a large number of onerous load combinations. These loads include gravitational, temperature, pressure and environmental loads along with various imposed displacements. Additionally, there are several design constraints that must be satisfied. Due to the three-dimensional geometric freedom of the spool there are many possible design scenarios that could be evaluated in the search for the optimum solution.
It is the responsibility of the pipeline design engineer to use their own judgment and experience to find the best possible solution within the design period. Traditionally a trial and error design approach is used in an iterative manner. This method is typically slow and labor intensive and can be too focused on one design concept at the expense of others that are potentially superior. On similar engineering problems with many design parameters automated non-linear optimization routines have been shown to be very effective. Specifically, applying evolutionary algorithms is a robust, time-effective and adaptable approach. Such a tool assists the engineer in finding superior design solutions and assists in searching the entire design space.
To test this design method, a multi-objective evolutionary algorithm has been applied to two semi-constrained spool design problems. The spool design has been modeled using finite element analysis. First, the algorithm was applied to the optimization of spool geometry for multiple design objectives. Within 24-hours of runtime the algorithm was able to find superior solutions to those found using a traditional iterative approach. Also, the trade-off between conflicting design objectives could be quantified and visualized to enable the designer to select the most appropriate candidate. The second problem evaluated was the placement of supports to mitigate the onset of vortex induced vibration (VIV). The algorithm was again able to quickly find a better solution and quantify the tradeoff between conflicting design objectives. The paper presents the results of this new design process as applied by subsea pipeline engineers to find optimum spool designs.