基于遗传算法的核级管道力学性能优化研究
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摘要
在核蒸汽供应系统中,核级管道数量众多且布置复杂。为使核级管道能满足设计规范,对支架位置及功能进行优化是设计过程中的重要环节。传统的优化过程通过大量的人工试算完成,该过程人力成本高且严重依赖工程经验,更重要的是难以得到力学性能最优布置方案。本文提出了一种基于遗传算法的智能优化布置方法,该方法通过将管道力学分析与遗传算法结合,实现了管道优化布置的自动化。结果显示,该方法能有效地对多个支架位置和功能进行同步优化,并快速获得力学性能最优的布置方案,与传统方法相比具有更高的效率和实用性。
In the nuclear steam supply system, the magnitude of nuclear piping is large and their layout are complicated. In order to keep the nuclear piping satisfing the design requirements, the optimization of the location and function of supports on the piping is significant during the design. The traditional method for optimization is manually trial calculation. The limitations of traditional method are high labor costs and experience dependency. Moreover, it is hard to obtain layout scheme with best mechanical property in the traditional method. In present work, a genetic algorithm based intelligent optimization method for piping layout is proposed. The mechanical analysis and genetic algorithm is combined in the present method, and the optimization process becomes automatic. The results show that this method can optimize the location and function of supports effectively. Comparing with traditional method, the present method is more efficiency and more practical.
In the nuclear steam supply system, the magnitude of nuclear piping is large and their layout are complicated. In order to keep the nuclear piping satisfing the design requirements, the optimization of the location and function of supports on the piping is significant during the design. The traditional method for optimization is manually trial calculation. The limitations of traditional method are high labor costs and experience dependency. Moreover, it is hard to obtain layout scheme with best mechanical property in the traditional method. In present work, a genetic algorithm based intelligent optimization method for piping layout is proposed. The mechanical analysis and genetic algorithm is combined in the present method, and the optimization process becomes automatic. The results show that this method can optimize the location and function of supports effectively. Comparing with traditional method, the present method is more efficiency and more practical.
引文
[1]王新军,卢喜丰,艾红雷,等.核级高能管道系统优化分析[J].核动力工程,2014,35(4):114-118.
[2]Chiba T,Okado S,Fujii I,et al.Optimum support arrangement of piping systems using genetic algorithm[J].Journal of Pressure Vessel Technology,1996,118(3):507-512.
[3]Collina A,Zanaboni P,Belloli M.On the optimization of support positioning and stiffness for piping systems on power plants[C].18th International Conference on Structural Mechanics in Reactor Technology,2005.
[4]Mahinthakumar G,Kripakaran Pm Baugh J,et al.Genetic algorithm-based decision support for optimizing seismic response of piping systems[J].Journal of structural engineering.2005,131(4):389-398.
[5]匡芳君.群智能混合优化算法及其应用研究[D].南京:南京理工大学学位论文,2014.
[6]Holland J H.Adaptation in natural and artificial systems[M].Ann Arbor:University of Michigan Press,1975.
[7]AFCEN.Design and Construction Rules for Mechanical Components of PWR Nuclear Islands,RCC-M Section I:Subsection C[S].2002.
[2]Chiba T,Okado S,Fujii I,et al.Optimum support arrangement of piping systems using genetic algorithm[J].Journal of Pressure Vessel Technology,1996,118(3):507-512.
[3]Collina A,Zanaboni P,Belloli M.On the optimization of support positioning and stiffness for piping systems on power plants[C].18th International Conference on Structural Mechanics in Reactor Technology,2005.
[4]Mahinthakumar G,Kripakaran Pm Baugh J,et al.Genetic algorithm-based decision support for optimizing seismic response of piping systems[J].Journal of structural engineering.2005,131(4):389-398.
[5]匡芳君.群智能混合优化算法及其应用研究[D].南京:南京理工大学学位论文,2014.
[6]Holland J H.Adaptation in natural and artificial systems[M].Ann Arbor:University of Michigan Press,1975.
[7]AFCEN.Design and Construction Rules for Mechanical Components of PWR Nuclear Islands,RCC-M Section I:Subsection C[S].2002.