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泵站正向进水结构流场特性多目标优化研究
引用本文:徐存东,胡小萌,王荣荣,王鑫,田俊姣. 泵站正向进水结构流场特性多目标优化研究[J]. 水利学报, 2024, 55(2): 167-178
作者姓名:徐存东  胡小萌  王荣荣  王鑫  田俊姣
作者单位:浙江水利水电学院, 浙江 杭州 310018;华北水利水电大学 水利学院, 河南 郑州 450046;河南大学 土木建筑学院, 河南 开封 475004
基金项目:中原科技创新领军人才支持计划项目(204200510048);浙江省基础公益研究计划项目(LZJWD22E090001);浙江省重点研发计划项目(2021C03019);宁夏回族自治区水利科技项目(GKGK-KY-2023-002)
摘    要:为提高引黄灌区水源含沙提水泵站进水结构流场稳定性,对泵站原型(泥沙淤积前)进水结构设计参数进行耦合协同优化。选取甘肃省景电灌区典型正向进水泵站为研究对象,确定流场特性评价指标与进水结构设计参数,基于仿真智能算法(PSO-BPNN)和多岛遗传算法(MIGA)构建PSO-BPNN-MIGA耦合优化模型,通过Realizable k-ε湍流模型耦合考虑相间滑移的Mixture多相流模型对最优方案进行模拟。由耦合优化模型得到的最优设计方案(OPT)为:扩散角θ=26.30°、总宽度B=26.46 m、底部纵坡i=1∶2.3、悬空高度C=1.05 m、淹没深度hs=1.38 m、后壁距T=0.57 m; OPT方案评价指标预测值和计算值的偏差率均在10.00%以内;OPT方案下泵站进水结构内未出现明显旋涡回流区,泥沙淤积强度和淤积范围明显减少、水流流速较小、流线较为均匀。优化模型在泵站原型进水结构协调优化中较为可靠,可实现参数区间内的全局连续寻优,所得最优方案整体优化效果较好。本文提出的研究思路与方法可为类似泵站工程设计参数耦合协同优化提供参考方法借鉴。

关 键 词:正向进水结构  流场特性  PSO-BPNN算法  MIGA算法  多目标优化  数值模拟
收稿时间:2023-09-06

Multi-objective optimization study of flow field characteristics in forward intake structure of pumping station
XU Cundong,HU Xiaomeng,WANG Rongrong,WANG Xin,TIAN Junjiao. Multi-objective optimization study of flow field characteristics in forward intake structure of pumping station[J]. Journal of Hydraulic Engineering, 2024, 55(2): 167-178
Authors:XU Cundong  HU Xiaomeng  WANG Rongrong  WANG Xin  TIAN Junjiao
Affiliation:Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China;School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450046, China;School of Civil Engineering and Architecture, Henan University, Kaifeng 475004, China
Abstract:To improve the stability of the flow field in the intake structure of the sand-laden pumping station in the Yellow River Irrigation District, the design parameters of the intake structure of the prototype pumping station (before sediment deposition) are coupled, and synergistically optimized.A typical positive inlet pumping station in Jingdian irrigation area of Gansu Province is selected as the research object, the flow field characteristics evaluation indexes and inlet structure design parameters are determined, the PSO-BPNN-MIGA coupled optimization model is constructed based on simulation intelligent algorithm (PSO-BPNN) and multi-island genetic algorithm (MIGA), and the optimal solution is optimized by Realizable k-ε turbulence model coupled with the inter-phase slip consideration.The optimal solution is simulated by the Realizable turbulence model coupled with the Mixture multiphase flow model considering the interphase slip.The optimal design scheme (OPT) obtained from the coupled optimization model is:diffusion angle θ=26.30°, total width B=26.46 m, bottom longitudinal slope i=1:2.3, overhang height C=1.05 m, inundation depth hs=1.38 m, back wall distance T=0.57 m;the deviation rates of the predicted and calculated values of the OPT scheme evaluation indexes are within 10.00%.There is no obvious vortex backflow area in the inlet structure of the pumping station under OPT scheme, and the sediment siltation intensity and siltation range are significantly reduced, the flow velocity is smaller and the flow line is more uniform.The optimization model is more reliable in the coordinated optimization of the prototype intake structure of the pumping station, and can realize the global continuous optimization in the parameter interval, and the overall optimization effect of the obtained optimal scheme is good.The research ideas and methods proposed in this paper can provide reference methods for the collaborative optimization of similar pumping station engineering design parameters coupling.
Keywords:forward intake structure  flow field characteristics  PSO-BPNN algorithm  MIGA algorithm  multi-objective optimization  numerical simulation
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