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OPTIMISATION OF SUBSEA TIE-IN SPOOLS USING EVOLUTIONARY ALGORITHMS

机译:基于进化算法的浅层结合体优化

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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.
机译:搭接线轴必须设计成能够抵抗大量繁重的载荷组合。这些负载包括重力,温度,压力和环境负载以及各种施加的位移。此外,必须满足几个设计约束。由于阀芯的三维几何自由度,在寻求最佳解决方案时可以评估许多可能的设计方案。管道设计工程师有责任使用自己的判断力和经验在设计期内找到最佳解决方案。传统上,尝试和错误设计方法是以迭代方式使用的。这种方法通常很慢且劳动强度大,并且可能过于专注于一个设计概念,而以牺牲其他潜在的优势为代价。在具有许多设计参数的类似工程问题上,自动化非线性优化例程已被证明非常有效。具体而言,应用进化算法是一种健壮,高效且适应性强的方法。这样的工具可帮助工程师找到出色的设计解决方案,并有助于搜索整个设计空间。为了测试该设计方法,将多目标进化算法应用于两个半约束阀芯设计问题。阀芯设计已使用有限元分析进行建模。首先,将该算法应用于针对多个设计目标的线轴几何优化。在24小时的运行时间内,该算法能够找到优于使用传统迭代方法找到的解决方案的解决方案。同样,可以对冲突的设计目标之间的权衡进行量化和可视化,以使设计人员能够选择最合适的候选人。评估的第二个问题是放置支撑物以减轻涡激振动(VIV)的发作。该算法再次能够快速找到更好的解决方案,并量化冲突的设计目标之间的权衡。本文介绍了海底管道工程师应用该新设计过程的结果,以找到最佳的阀芯设计。

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