摘要
为缓解目前黄河下游管道输沙距离短、能效低等问题,针对长距离管道输沙问题,基于阻力损失与流速的变化特性,建立了以输沙量偏差和流速偏差为目标函数,以满足泥沙浓度、流速、管径、输沙量等方面要求为约束条件的多目标优化模型。通过黄河下游管道输沙实例,选用NSGA-Ⅱ遗传算法进行多目标寻优,得到的Pareto最优解集和最优前沿在取值空间内呈连续均匀分布,且输沙量偏差向目标函数高效收敛。根据泥沙体积分数不同将所得解集分为3组输沙方案,以适应动态变化的水沙条件和工程需求。
In order to mitigate the problems of short distance and low energy efficiency for the pipeline sediment transport in the lower Yellow River floodplain,a multi⁃objective optimization model was built for pipeline design for the sediment transport in the Yellow River floodplain.The model consisted of two objective functions(sediment discharge deviation and flow velocity deviation)and four constrains(sediment con⁃centration,flow velocity,pipe diameter and sediment discharge).NSGA-Ⅱgenetic algorithm was chosen for resolving multi⁃objective opti⁃mization model.The case study shows that the Pareto optimal solution set and the optimal frontier are distributed continuously and uniformly in the value space.Moreover,the deviation function of sediment transport has better convergence.According to the sediment concentration,the solution set was divided into three groups to adapt to the variation of water and sediment conditions and engineering requirements.
作者
刘一鸣
姜晗琳
李振山
LIU Yiming;JIANG Hanlin;LI Zhenshan(Key Laboratory of Water and Sediment Sciences of the Ministry of Education,College of Environmental Science and Engineering,Peking University,Beijing 100871,China)
出处
《人民黄河》
CAS
北大核心
2021年第5期30-34,41,共6页
Yellow River
基金
国家重点研发计划项目(2016YFC0402505)。
关键词
泥沙
黄河下游
管道输送
多目标优化
遗传算法
sediment
Lower Yellow River
pipeline transportation
multi⁃objective optimization
genetic algorithm
