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LAYOUT OPTIMIZATION OF BRANCH PIPELINE NETWORK ON CURVED SURFACE USING GENETIC ALGORITHM

机译:遗传算法在曲面曲面支管网络布局优化中的应用

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Branch structure is common in oil and gas field gathering system. The rational determination of the pipe network structure and pipelines trend is an important part of the gathering system design. The previous optimization of tree structure is usually studied under two dimensions and the distances between stations, which are represented by straight lines. The study can neither correctly reflect the real situation nor get the optimal solution, because of the dramatic topographic. This paper firstly deals with the shortest route issue on a curved surface. The common way to solve the problem is variational method. However, the method relies on the surface function, which becomes the constraints hard to deal with. The author would obtain the optimal route between two points with the genetic algorithm. Both steady state (SS) and generational (GN) GAs were implemented for the test problem. The performance of a GA generally depends on the selected GA parameters, in particular the crossover and mutation probabilities. Based on the variation of crossover and mutation probability CP and MP in the range of 0.4-1.0 and 0.0005-0.3, the sensitivity of GA to the Gas was therefore established. The best solution has been found by GN GA based on the average evaluation value of the best solutions, which obtained from fifty independent GA runs. According to the case analysis, a 21.73% reduction in total length of the pipeline has been found by using GA. The results presented show that the GA is a robust and stable technique for the solution of route optimization problem. According to further study, the practice of engineering designs are often carried out under two dimensions by using minimum spanning tree algorithm to realize the layout optimization of pipe network. On a curved surface, with the GA above, one can get the trends of each pipe section without changing the connection relationship and the total length of the network is reduced by 12.21%. Yet the connection within a plane cannot guarantee the optimum solution, thus the paper developed the optimization model of branch structure distribution within a curved surface. According to the case analysis, the previous connection relationship between points has been changed, further reducing the total length by 0.97%. In conclusion, the technique in this paper can determine the optimal pipeline laying route, effectively develop the network structure and reduce the total length of pipelines.
机译:分支结构在油气田采集系统中很常见。合理确定管网结构和管道趋势是采集系统设计的重要组成部分。通常在二维和站点之间的距离(以直线表示)的基础上研究树结构的先前优化。由于地形变化剧烈,因此该研究既不能正确反映实际情况,也无法获得最佳解决方案。本文首先研究曲面上的最短路径问题。解决问题的常用方法是变分法。然而,该方法依赖于表面功能,这成为难以处理的约束。作者将使用遗传算法获得两点之间的最佳路线。对于测试问题,均实现了稳态(SS)和世代(GN)GA。 GA的性能通常取决于所选的GA参数,尤其是交叉和突变概率。因此,基于交叉和变异概率CP和MP在0.4-1.0和0.0005-0.3之间的变化,可以确定GA对Gas的敏感性。 GN GA根据最佳解决方案的平均评估值找到了最佳解决方案,该平均值是从五十次独立的GA运行获得的。根据案例分析,使用遗传算法发现管道总长度减少了21.73%。提出的结果表明,遗传算法是一种解决路由优化问题的可靠且稳定的技术。根据进一步的研究,工程设计的实践通常是在二维空间内通过最小生成树算法来实现管网的布局优化。在曲面上,通过使用GA,可以在不更改连接关系的情况下获得每个管段的趋势,并且网络的总长度减少了12.21%。然而,平面内的连接并不能保证最优解,因此本文建立了曲面内分支结构分布的优化模型。根据案例分析,以前的点之间的连接关系已更改,进一步将总长度减少了0.97%。综上所述,本文所提出的技术可以确定最优的管道铺设路线,有效地发展网络结构,减少管道总长度。

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