Multi-objective shape optimization of runner blade for Kaplan turbine

被引:18
|
作者
Semenova, A. [1 ]
Chirkov, D. [2 ]
Lyutov, A. [2 ]
Cherny, S. [2 ]
Skorospelov, V. [3 ]
Pylev, I. [1 ]
机构
[1] OJSC Power Machines LMZ, St Petersburg, Russia
[2] SB RAS, Inst Computat Technol, Novosibirsk, Russia
[3] SB RAS, Inst Math, Novosibirsk, Russia
关键词
D O I
10.1088/1755-1315/22/1/012025
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Automatic runner shape optimization based on extensive CFD analysis proved to be a useful design tool in hydraulic turbomachinery. Previously the authors developed an efficient method for Francis runner optimization. It was successfully applied to the design of several runners with different specific speeds. In present work this method is extended to the task of a Kaplan runner optimization. Despite of relatively simpler blade shape, Kaplan turbines have several features, complicating the optimization problem. First, Kaplan turbines normally operate in a wide range of discharges, thus CFD analysis of each variant of the runner should be carried out for several operation points. Next, due to a high specific speed, draft tube losses have a great impact on the overall turbine efficiency, and thus should be accurately evaluated. Then, the flow in blade tip and hub clearances significantly affects the velocity profile behind the runner and draft tube behavior. All these features are accounted in the present optimization technique. Parameterization of runner blade surface using 24 geometrical parameters is described in details. For each variant of runner geometry steady state three-dimensional turbulent flow computations are carried out in the domain, including wicket gate, runner, draft tube, blade tip and hub clearances. The objectives are maximization of efficiency in best efficiency and high discharge operation points, with simultaneous minimization of cavitation area on the suction side of the blade. Multiobjective genetic algorithm is used for the solution of optimization problem, requiring the analysis of several thousands of runner variants. The method is applied to optimization of runner shape for several Kaplan turbines with different heads.
引用
收藏
页数:10
相关论文
共 50 条
  • [31] Multi-objective optimization design on high pressure side of a pump-turbine runner with high efficiency
    School of Energy Science and Engineering, Harbin Institute of Technology, Harbin
    150001, China
    不详
    150040, China
    [J]. Renew. Energy, 2022, (103-120):
  • [32] Multi-objective optimization of a bidirectional impulse turbine
    Badhurshah, Rameez
    Samad, Abdus
    [J]. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART A-JOURNAL OF POWER AND ENERGY, 2015, 229 (06) : 584 - 596
  • [33] An Agent Based Approach for Multi-Objective Optimization in Production Scheduling for Turbine Engine Blade Manufacturing
    Lu, Ruiqiang
    [J]. SAE INTERNATIONAL JOURNAL OF MATERIALS AND MANUFACTURING, 2015, 8 (01) : 12 - 17
  • [34] NUMERICAL INVESTIGATION AND MULTI-OBJECTIVE STRUCTURE OPTIMIZATION OF TRANSPIRATION COOLING ON THE LEADING EDGE OF TURBINE BLADE
    Liu, Taolue
    He, Fei
    Wu, Xiaorong
    Zhou, Zhizhao
    He, Yang
    Wang, Jianhua
    [J]. PROCEEDINGS OF ASME TURBO EXPO 2024: TURBOMACHINERY TECHNICAL CONFERENCE AND EXPOSITION, GT2024, VOL 7, 2024,
  • [35] Multi-objective differential evolution optimization based on uniform decomposition for wind turbine blade design
    Wang, Long
    Wang, Tongguang
    Wu, Jianghai
    Chen, Guoping
    [J]. ENERGY, 2017, 120 : 346 - 361
  • [36] Rapid multidisciplinary, multi-objective optimization of composite horizontal-axis wind turbine blade
    Jelena, Svorcan
    Zorana, Trivkovic
    Marija, Baltic
    Ognjen, Pekovic
    [J]. PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE MULTIDISCIPLINARY ENGINEERING DESIGN OPTIMIZATION (MEDO), 2016,
  • [37] Multi-objective structural optimization of a HAWT composite blade
    Dal Monte, Andrea
    Castelli, Marco Raciti
    Benini, Ernesto
    [J]. COMPOSITE STRUCTURES, 2013, 106 : 362 - 373
  • [38] Multi-objective optimization of the airfoil shape of Wells turbine used for wave energy conversion
    Mohamed, M. H.
    Janiga, G.
    Pap, E.
    Thevenin, D.
    [J]. ENERGY, 2011, 36 (01) : 438 - 446
  • [39] MULTI-OBJECTIVE OPTIMIZATION OF RUNNER BLADES USING A MULTI-FIDELITY ALGORITHM
    Bahrami, Salman
    Tribes, Christophe
    Devals, Christophe
    Vu, Thi C.
    Guibault, Francois
    [J]. PROCEEDINGS OF THE ASME POWER CONFERENCE, 2013, VOL 2, 2014,
  • [40] A Hybrid Method for Multi-Objective Shape Optimization
    Kumar, G. N. Sashi
    Mahendra, A. K.
    Sanyal, A.
    Gouthaman, G.
    [J]. SIMULATED EVOLUTION AND LEARNING, 2010, 6457 : 563 - 567