摘要
本文将遗传算法和变密度各项异性湍浮力射流模型有机结合,提出了满足最佳稀释效果和最低能源消耗的射流比与射流喷角多参数多目标非线性遗传优化耦合反演的新方法:将射流模型和运行能源消耗公式嵌入到遗传算法模型中,以最佳污水稀释效果和最低能源消耗为目标,进行射流模型多参数的优化耦合反演。研究结果表明基于非线性遗传优化的多参数多目标耦合反演方法可以获得最优的射流参数,有利于提高射流水体与环境水体间的掺混效果,降低污水输送能源消耗。
This paper presents a new multi-parameter and multi-object nonlinear genetic optimal coupled inversion method coupling an genetic algorithm with an anisotropic turbulent model to calculate the jet ratio and jet angle of a buoyant jet with variable density. This method considers optimal dilution effect and lowest energy consumption by embedding the jet model and operation energy consumption equation into the genetic algorithm, and obtains optimal multi-parameters through multi-object optimization. The results show that the inversion method has advantages of jet parameter optimization that enhances jet water mixing with environment water and reduces energy consumption.
出处
《水力发电学报》
EI
CSCD
北大核心
2014年第4期92-97,共6页
Journal of Hydroelectric Engineering
基金
国家自然科学基金资助项目(51209110)
天津市科技兴海项目(KJXH2011-17)
大连理工大学海岸和近海工程国家重点实验室研究基金资助项目(LP1108)
中央级公益性科研院所基本科研业务费专项资金项目(TKS100217
KJFZJJ2011-01
TKS130215)
关键词
环境水力学
射流模型
多目标
非线性遗传优化耦合反演
射流比
射流喷角
environmental hydraulics
jet model
multi-object
nonlinear genetic optimal coupled inversion
jet ratio
jet angle
