ACTIVE CONTROL OF VORTEX-INDUCED VIBRATION OF CYLINDR BASED ON VELOCITY AND DISPLACEMENT FEEDBACK
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摘要: 以单自由度二维圆柱为研究对象, 将速度反馈与位移反馈加入涡激振动理论模型中, 探究了速度反馈和位移反馈控制规律, 同时引入智能算法, 利用神经网络将流场信息映射到反馈增益大小, 采用遗传算法优化神经网络参数, 从而得到不同折合流速 ($ {U_r} $ = 3.5 ~ 8)下速度反馈与位移反馈较优组合, 由此提出圆柱涡激振动增强策略, 进而实现不同流速下圆柱涡激振动主动控制. 研究表明: 速度反馈与位移反馈为涡激振动系统提供了能量源, 激发了圆柱的振动和漩涡脱落, 使涡激振动的起振时间要早于未受控状态, 且振动频率高于未受控状态, 使圆柱的涡脱频率不再受圆柱固有频率的支配, 最终实现了在折合流速范围 $ {U_r} $ = 3.5 ~ 8 内使圆柱的振动幅值比稳定保持在目标振幅比(0.6 ~ 0.8)内, 这一结果说明外部激励能够控制结构的振动速度和起振时间; 同时将反馈增益约束引入智能控制算法模型中, 对原计算模型进一步优化, 使平均能耗 J 较无约束情况降低了 33.08%, 极大地减少了主动控制过程的能耗. 本研究可实现主动控制钝体涡激振动增强, 将有益于更有效地捕获风振能量.Abstract: Taking a single degree of freedom two-dimensional cylinder as the research object, the velocity feedback and displacement feedback are added to the vortex-induced vibration theory model, and the control laws of velocity feedback and displacement feedback are explored. At the same time, intelligent algorithm is introduced, neural network is used to map the flow field information to the feedback gain, and genetic algorithm is used to optimize the neural network parameters, so as to obtain the optimal combination of velocity feedback and displacement feedback under different reduced flow rates ($ {U_r} $ = 3.5 ~ 8). Therefore, the cylindrical vortex-induced vibration enhancement strategy is proposed, and then the active control of cylindrical vortex-induced vibration under different flow rates is realized. The results show that the velocity feedback and displacement feedback provides an energy source for the vortex-excited vibration system, and stimulates the vibration of the cylinder and the vortex shedding, so that the onset time of the vortex-excited vibration under controlled is earlier than the uncontrolled state, and the vibration frequency under controlled is higher than the uncontrolled state, beside that, the vorticity frequency of a cylinder is no longer dominated by the natural frequency of the cylinder, and the vibration amplitude ratio of the cylinder is maintained at target amplitude ratio (0.6 ~ 0.8) in the range of referred flow rate $ {U_r} $ = 3.5 ~ 8 in the end. These consequences indicates that the external excitation control can increase the vibration speed and start-up time of the structure. At the same time, the feedback gain constraint is introduced into the intelligent control algorithm model, and the original calculation model is further optimized, so that the average energy consumption J is reduced by 33.08% compared with the unconstrained condition. The feedback gain constraint greatly reduces the energy consumption of the active control process. This study can realize active control of vorticity vibration enhancement of blunt body, it will be beneficial to capture wind vibration energy.
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Key words:
- cylinder /
- vortex-induced vibration /
- active control /
- genetic algorithms /
- neural networks
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图 1 二维涡激振动系统结构示意图
Figure 1. Schematic diagram of a two-dimensional vortex-induced vibration system
图 2 利用遗传算法寻找最优的神经网络结构参数的计算框架
Figure 2. A computational framework for the optimal neural network structural parameters by employing the genetic algorithm
图 3 不同种群数量对最大适应值的影响
Figure 3. The effect of different population sizes on maximum adaptation values
图 4 计算域, 边界条件和网格组成示意图
Figure 4. Schematic diagram of computational domain, boundary condition and mesh composition
图 6 本文数值仿真结果与实验结果和文献结果对比
Figure 6. The numerical simulation results are compared with the experimental results and literature results
图 7 速度反馈和位移反馈对振幅比的影响
Figure 7. The effect of velocity feedback and displacement feedback on vibration amplitude ratio
7 速度反馈和位移反馈对振幅比的影响 (续)
7. The effect of velocity feedback and displacement feedback on vibration amplitude ratio (continued)
图 8 折合流速$ {U_r} $ = 2.5 ~ 14.5时, 圆柱在4种神经网络的4×10组输出增益下涡激振动幅值比 (续)
Figure 8. The amplitude ratio of vortex-induced vibration of the cylinder under the output gain of 4 × 10 groups of 4 neural networks (Ur=2.5 ~ 14.5) (continued)
图 9 不施加约束和施加约束情况下10个不同的样本的J值, 种群数量为100
Figure 9. J values for 10 different samples without and with constraints imposed, the population size is 100
图 10 (a) ~ (b)施加反馈约束后的输出反馈增益以及(c) ~ (f)反馈增益下的振动幅值比
Figure 10. (a) ~ (b) Output feedback gain with feedback constraint applied and (c) ~ (f) vibration amplitude ratio at feedback gain
图 11 圆柱振动涡量图, “ + ”符号表示圆柱的平衡位置
Figure 11. Vibration vortex structures of the cylinder , The symbol “+” indicates the equilibrium position of the cylinder
图 12 圆柱振动位移和速度相图
Figure 12. Diagram of vibration displacement and velocity of the cylinder
图 13 折合流速$ {U_r} $ = 3.5, 8时, 圆柱的振动位移和升力系数时间历程变化曲线
Figure 13. The time history of the vibration displacement and lift coefficient of the cylinder (Ur =3.5, 8)
图 14 圆柱位移和升力的频谱图
Figure 14. Spectrogram of displacement and lift force of the cylinder
表 1 计算模型参数
Table 1. The parameters of computational model
Name m/kg D/m $ \xi $ ω0/(rad·s−1) $ {\rho _f} $/(kg·m−3) CL0 CD λ P St size 0.001 0.02 0.000 5 62.83 1.29 0.3 1.2 0.3 12 0.2 
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表 2 遗传算法参数设置
Table 2. Genetic algorithm parameters
Genetic algorithm parameter Evolution generation Population size Individuals of tournament selection Crossover rate Mutation rate number 30 100 6 0.7 0.45
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表 3 重叠网格数量无关性验证(无反馈控制, ${{\boldsymbol{U}}_{\boldsymbol{r}}}$ = 5)
Table 3. Validation of the number of overlapping meshes (no feedback control, $ {U_r} $ = 5)
Grid type Background grid (H × H) Foreground grid
(L × d)Number of grids Time steps (∆t) Amplitude ratio (A/D) M1 150 × 150 50 × 160 66 153 0.003 s 0.686 M2 200 × 200 80 × 240 104 353 0.003 s 0.694 (1.166%) M3 250 × 250 100 × 320 169 043 0.003 s 0.697 (0.432%) M4 200 × 200 80 × 240 104 353 0.001 s 0.690 (0.576%) M5 200 × 200 80 × 240 104 353 0.006 s 0.652 (6.052%)
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[1] 王同光, 田琳琳, 钟伟等. 风能利用中的空气动力学研究进展Ⅰ: 风力机气动特性. 空气动力学学报, 2022, 40(4): 1-21 (Wang Tongguang, Tian Linlin, Zhong Wei. Research progress on aerodynamics in wind energy utilization I: Aerodynamic characteristics of wind turbines. Acta Aerodynamica Sinica, 2022, 40(4): 1-21 (in Chinese)Wang Tongguang, Tian Linlin, Zhong Wei. Research progress on aerodynamics in wind energy utilization I. : aerodynamic characteristics of wind turbines. Acta Aerodynamica Sinica, 2022, 40(4): 1-21(in Chinese) [2] Gabbai RD, Benaroya H. An overview of modeling and experiments of vortex-induced vibration of circular cylinders. Journal of Sound and Vibration, 2005, 282(3-5): 575-616 doi: 10.1016/j.jsv.2004.04.017 [3] Sarpkaya T. A critical review of the intrinsic nature of vortex-induced vibrations. Journal of Fluids and Structures, 2004, 19(4): 389-447 doi: 10.1016/j.jfluidstructs.2004.02.005 [4] Bernitsas MM, Raghavan K, Ben-Simon Y, et al. VIVACE (vortex induced vibration aquatic clean energy): A new concept in generation of clean and renewable energy from fluid flow. Journal of Offshore Mechanics and Arctic Engineering, 2008, 130(4): 041101 doi: 10.1115/1.2957913 [5] El-Shahat A. Bladeless wind turbine as wind energy possible future technology. Natural Gas & Electricity, 2016, 33(4): 16-20 [6] Bahmani MH, Akbari MH. Effects of mass and damping ratios on VIV of a circular cylinder. Ocean Engineering, 2010, 37(5-6): 511-519 doi: 10.1016/j.oceaneng.2010.01.004 [7] Barrero-Gil A, Pindado S, Avila S. Extracting energy from vortex-induced vibrations: A parametric study. Applied Mathematical Modelling, 2012, 36(7): 3147-3154 [8] 邹琳, 秦傲, 杨耀宗等. 波浪锥型圆柱流固耦合振动机理研究. 振动与冲击, 2022, 41(3): 18-26 (Zou Lin, Qin Ao, Yang Yaozong, et al. Fluid-structure coupled vibration mechanism of wave conical cylinder. Journal of Vibration and Shock, 2022, 41(3): 18-26 (in Chinese)Zou Lin, Qin Ao, Yang Yaozong, et al. Fluid-structure coupled vibration mechanism of wave conical cylinder. Journal of Vibration and Shock, 2022, 41(3): 18-26 (in Chinese) [9] Zhang B, Mao Z, Song B, et al. Numerical investigation on VIV energy harvesting of four cylinders in close staggered formation. Ocean Engineering, 2018, 165: 55-68 doi: 10.1016/j.oceaneng.2018.07.042 [10] Quadrante LAR, Nishi Y. Amplification/suppression of flow-induced motions of an elastically mounted circular cylinder by attaching tripping wires. Journal of Fluids and Structures, 2014, 48: 93-102 doi: 10.1016/j.jfluidstructs.2014.02.018 [11] Nishi Y, Luis ARQ. Attachment of tripping wires to enhance the efficiency of a vortex-induced vibrations energy generation system. Journal of Power and Energy Systems, 2013, 7(3): 162-176 doi: 10.1299/jpes.7.162 [12] Kiu KY, Stappenbelt B, Thiagarajan KP. Effects of uniform surface roughness on vortex-induced vibration of towed vertical cylinders. Journal of Sound and Vibration, 2011, 330(20): 4753-4763 doi: 10.1016/j.jsv.2011.05.009 [13] Mackowski AW, Williamson CHK. An experimental investigation of vortex-induced vibration with nonlinear restoring forces. Physics of Fluids, 2013, 25(8): 087101 [14] Huynh B, Tjahjowidodo T, Zhong Z, et al. Nonlinearly enhanced vortex induced vibrations for energy harvesting//IEEE International Conference on Advanced Intelligent Mechatronics (AIM). Busan, South Korea, 2015: 91-96 [15] Ramlan R, Brennan MJ, Mace BR, et al. Potential benefits of a non-linear stiffness in an energy harvesting device. Nonlinear Dynamics, 2010, 59(4): 545-558 doi: 10.1007/s11071-009-9561-5 [16] Huynh BH, Tjahjowidodo T, Zhong ZW, et al. Design and experiment of controlled bistable vortex induced vibration energy harvesting systems operating in chaotic regions. Mechanical Systems and Signal Processing, 2018, 98(1): 1097-1115 [17] Huynh BH, Tjahjowidodo T. Experimental chaotic quantification in bistable vortex induced vibration systems. Mechanical Systems and Signal Processing, 2017, 85: 1005-1019 doi: 10.1016/j.ymssp.2016.09.025 [18] Brunton SL, Noack BR, Koumoutsakos P. Machine learning for fluid mechanics. Annual Review of Fluid Mechanics, 2020, 52(1): 477-508 doi: 10.1146/annurev-fluid-010719-060214 [19] Johannink T, Bahl S, Nair A, et al. Residual reinforcement learning for robot control//International Conference on Robotics and Automation. Montreal, QC, Canada , 2019: 6023-6029 [20] Zhou M, Yu Y, Qu X. Development of an efficient driving strategy for connected and automated vehicles at signalized intersections: a reinforcement learning approach. IEEE Transactions on Intelligent Transportation Systems, 2020, 21(1): 433-443 doi: 10.1109/TITS.2019.2942014 [21] Ren FW, Tang CL, Tang HH. Active control of vortex-induced vibration of a circular cylinder using machine learning. Physics of Fluids, 2019, 31(9): 093601 doi: 10.1063/1.5115258 [22] Paris R, Beneddine S, Dandois J. Robust flow control and optimal sensor placement using deep reinforcement learning. Journal of Fluid Mechanics, 2021, 913: A25 [23] 任峰. 针对圆柱涡激振动问题的智能流动控制. 水动力学研究与进展A辑, 2022, 37(6): 757-762 (Ren Feng. Intelligent flow control for vortex-induced vibration of cylinder. Chinese Journal of Hydrodynamics, 2022, 37(6): 757-762 (in Chinese)Ren Feng. Intelligent flow control for vortex-induced vibration of cylinder. Chinese journal of hydrodynamics, 2022, 37(6): 757-762 (in Chinese) [24] 陈国良. 遗传算法及其应用. 北京: 人民邮电出版社, 1996Chen Guoliang. Genetic Algorithms and Their Applications. Beijing: The People's Posts and Telecommunications Press, 1996 (in Chinese) [25] Li R, Noack B R, Cordier L, et al. Drag reduction of a car model by linear genetic programming control. Experiments in Fluids, 2017, 58(8): 103 [26] 陈东阳, 顾超杰, 朱卫军等. 抑制柱体结构涡激振动的非线性能量阱减振装置优化设计. 工程力学, 2020, 37(9): 240-247 (Chen Dongyang, Gu Chaojie, Zhu Weijun et al. An optimum design of nonlinear energy sink vibration absorbing device for suppressing vortex-induced vibration of cylindrical structures. Engineering Mechanics, 2020, 37(9): 240-247 (in Chinese)Chen Dongyang, Gu Chaojie, Zhu Weijun et al. An optimum design of nonlinear energy sink vibration absorbing device for suppressing vortex-induced vibration of cylindrical structures. Engineering Mechanics, 2020, 37(9): 240-247 (in Chinese) [27] Benard N, Pons-Prats J, Periaux J, et al. Turbulent separated shear flow control by surface plasma actuator: experimental optimization by genetic algorithm approach. Experiments in Fluids, 2016, 57(2): 22 doi: 10.1007/s00348-015-2107-3 [28] Minelli G, Dong T, Noack BR, et al. Upstream actuation for bluff-body wake control driven by a genetically inspired optimization. Journal of Fluid Mechanics, 2020, 893: A1 [29] 何长江, 段忠东. 二维圆柱涡激振动的数值模拟. 海洋工程, 2008, 26(1): 57-63 (He Changjiang, Duan Zhongdong. Numerical simulation of vortex-induced vibration on 2D circular cylinders. Engineering Mechanics, 2008, 26(1): 57-63 (in Chinese)He Changjiang, Duan Zhongdong. Numerical simulation of vortex-induced vibration on 2 D circular cylinders. Engineering Mechanics, 2008, 26(1): 57-63 (in Chinese) [30] Facchinetti ML, Langre ED, Biolley F. Coupling of structure and wake oscillators in vortex-induced vibrations. Journal of Fluids and Structures, 2004, 19(2): 123-140 [31] 陈东阳, 肖清, 顾超杰等. 柱体结构涡激振动数值计算. 振动与冲击, 2020, 39(19): 7-12, 47 (Chen Dongyang, Xiao Qing, Gu Chaojie et al. Numerical calculation of vortex-induced vibration of a cylinder structure. Journal of Vibration and Shock, 2020, 39(19): 7-12, 47 (in Chinese) doi: 10.1016/j.jfluidstructs.2003.12.004Chen Dongyang, Xiao Qing, Gu Chaojie et al. Numerical calculation of vortex-induced vibration of a cylinder structure. Journal of Vibration and Shock, 2020, 39(19): 7-12, 47 (in Chinese) doi: 10.1016/j.jfluidstructs.2003.12.004 [32] Langdon WB. Genetic programming and evolvable machines at 20. Genetic Programming & Evolvable Machines, 2020, 21(1-2): 205-217 [33] Singh SP, Mittal S. Vortex-induced oscillations at low Reynolds numbers: Hysteresis and vortex-shedding modes. Journal of Fluids and Structures, 2005, 20(8): 1085-1104 doi: 10.1016/j.jfluidstructs.2005.05.011 [34] 黄继露. 低雷诺数层流中串列双圆柱流致振动的数值模拟及其机理研究. [硕士论文]. 天津: 天津大学, 2012Huang Jilu. Numerical simulation of tandem double cylindrical flow-induced vibration in low Reynolds number laminar flow and its mechanism. [Master Thesis]. Tianjin: Tianjin University, 2012 (in Chinese) [35] Blevins RD, Coughran CS. Experimental investigation of vortex-induced vibration in one and two dimensions with variable mass, damping, and reynolds number. Journal of Fluids Engineering, 2009, 131(10): 101202 doi: 10.1115/1.3222904 -
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