Review Article

Micropower Generation Using Cross-Flow Instabilities: A Review of the Literature and Its Implications

[+] Author and Article Information
Mohammed F. Daqaq

Global Network,
New York University,
Abu Dhabi 129188, UAE
e-mail: mfd6@nyu.edu

Amin Bibo

Department of Mechanical Engineering,
Clemson University,
Clemson, SC 29634
e-mail: abibo@clemson.edu

Imran Akhtar

Department of Mechanical Engineering,
NUST College of Electrical and
Mechanical Engineering,
National University of Science and Technology,
Islamabad 44000, Pakistan
e-mail: imran.akhtar@ceme.nust.edu.pk

Ali H. Alhadidi

Department of Mechanical Engineering,
University of Jordan,
Amman 11942, Jordan
e-mail: ahadidi@ju.edu.jo

Meghashyam Panyam

Department of Mechanical Engineering,
Clemson University,
Clemson, SC 29634
e-mail: mpanyam@clemson.edu

Benjamin Caldwell

Michelin North America,
Greenville, SC 29602
e-mail: ben.caldwell@michelin.com

Jamie Noel

Department of Mechanical Engineering,
Clemson University,
Clemson, SC 29634
e-mail: jhnoel@clemson.edu

1Corresponding author.

Contributed by the Technical Committee on Vibration and Sound of ASME for publication in the JOURNAL OF VIBRATION AND ACOUSTICS. Manuscript received May 10, 2018; final manuscript received January 9, 2019; published online February 13, 2019. Assoc. Editor: Lei Zuo.

J. Vib. Acoust 141(3), 030801 (Feb 13, 2019) (27 pages) Paper No: VIB-18-1199; doi: 10.1115/1.4042521 History: Received May 10, 2018; Revised January 09, 2019

Emergence of increasingly smaller electromechanical systems with submilli-Watt power consumption led to the development of scalable micropower generators (MPGs) that harness ambient energy to provide electrical power on a very small scale. A flow MPG is one particular type which converts the momentum of an incident flow into electrical output. Traditionally, flow energy is harnessed using rotary-type generators whose performance has been shown to drop as their size decreases. To overcome this issue, oscillating flow MPGs were proposed. Unlike rotary-type generators which rely upon a constant aerodynamic force to produce a deflection or rotation, oscillating flow MPGs take advantage of cross-flow instabilities to provide a periodic forcing which can be used to transform the momentum of the moving fluid into mechanical motion. The mechanical motion is then transformed into electricity using an electromechanical transduction element. The purpose of this review article is to summarize important research carried out during the past decade on flow micropower generation using cross-flow instabilities. The summarized research is categorized according to the different instabilities used to excite mechanical motion: galloping, flutter, vortex shedding, and wake-galloping. Under each category, the fundamental mechanism responsible for the instability is explained, and the basic mathematical equations governing the motion of the generator are presented. The main design parameters affecting the performance of the generator are identified, and the pros and cons of each method are highlighted. Possible directions of future research which could help to improve the efficacy of flow MPGs are also discussed.

Copyright © 2019 by ASME
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Fig. 1

Power density at the rated speed and cost per unit area of rotary-type wind turbines

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Fig. 2

Feedback in fluid–structure interaction

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Fig. 3

Fundamentals of the fluid–structure interactions responsible for flow-induced vibration

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Fig. 4

Typical steady-state amplitude versus wind speed response of a galloping oscillator

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Fig. 5

Velocity streamlines around a trapezoid angled at 20 deg with respect to the incident flow. Dashed lines represent the shear layers.

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Fig. 6

Typical response of a wake-galloping oscillator

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Fig. 7

A complete cycle of spanwise vorticity contours for the cylinder undergoing VIV at Re = 104

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Fig. 8

Plunge and pitch of an airfoil exhibiting flutter

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Fig. 9

(a) A schematic diagram of a galloping flow MPG, the adjacent fluid, and (b) a typical output voltage curve

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Fig. 10

A schematic diagram of a lumped-parameters model of a galloping MPG: (a) oscillator, (b) piezoelectric transduction circuit representation, and (c) electromagnetic transduction circuit representation

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Fig. 11

The interpolating polynomial for Ca for a square body in smooth flow [42]. (Reproduced with permission from Ref. [66]. Copyright 2018 by AIP Publishing.)

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Fig. 12

Variation of Ca with α for four bluff profiles with a frontal width D facing the flow. Data from Ref. [157].

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Fig. 13

Response behavior of a galloping flow MPG. Results were obtained using A1 = 1, A3 = 10, μ = 0.5, and ζT = 0.01.

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Fig. 14

Variation of the optimal resistive load with κ/ζm for different reduced wind speeds U¯. Solid-line represents maxima and dashed-lines represent minima. (Reproduced with permission from Ref. [7]. Copyright 2014 by AIP Publishing).

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Fig. 15

Experimental universal response curve of galloping harvester with square-sectioned bluff body. Asterisks for steel beam results: blue (ωn = 3.09 Hz, ζm = 4.1 × 10−3), green (ωn = 3.59 Hz, ζm = 4.3 × 10−3), and red (ωn = 4.09 Hz, ζm = 3.9 × 10−3). Circles for Aluminum beam results: blue (ωn = 3.44 Hz, ζm = 3 × 10−3), and red (ωn = 3.44 Hz, ζm = 3 × 10−3). Solid line represents theoretical results. (Reproduced with permission from Ref. [7]. Copyright 2014 by AIP Publishing).

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Fig. 16

Experimental universal response curves of galloping harvesters with different bluff bodies. Squares for a square section, circles for D-shaped section, and triangles for a 53 deg isosceles-triangular section. Solid lines represent theoretical predictions. In all cases, the bluff body is oriented with the flat surface facing the wind. (Reproduced with permission from Ref. [7]. Copyright 2014 by AIP Publishing).

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Fig. 17

(a) Galloping flow MPG with 2DOFs cut-out cantilever proposed by Zhao et al. [68]; (b) galloping flow MPG with beam stiffener proposed by Zhao and Yang [69]; and (c) galloping flow MPG with nonlinear stiffness proposed by Bibo et al. [70]

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Fig. 18

A schematic diagram of a wake-galloping MPG

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Fig. 19

Variation of the output power of a capacitive wake-galloping flow MPG with the shedding frequency Ω. Results are obtained using ζm = 0.05, μ = 0.5, κ = 0.01, St = 1/(2π), ωn = 0.01, Cp = 1 × 10−6, and CF = 1.

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Fig. 20

(a) Wake-galloping flow MPG proposed by Wang et al. [95]. (b) Wake-galloping flow MPG proposed by Wang et al. [96]. (c) Wake-galloping flow MPG proposed by Jung and Lee [97].

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Fig. 21

Wake-galloping flow energy harvesting using a tandem of three harvesters placed behind each other [101]

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Fig. 22

Schematic of a the wake-galloping flow MPG proposed by Hobbs and Hu [102]

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Fig. 23

Contour plot of the total dimensionless power of the four cylinders as a function of frequency ratio fs/fn and the spacing L/D [102]. (Reproduced with permission from Ref. [102]. Copyright 2012 by Elsevier.)

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Fig. 24

Wake-galloping MPG with bistable restoring force proposed by Alhadidi and Daqaq [104]

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Fig. 25

Variation of the average power with the wind speed for the device proposed by Alhadidi and Daqaq [104]. (Reproduced with permission from Ref. [104]. Copyright 2016 by AIP Publishing).

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Fig. 26

Mean power output from a linear-spring and two nonlinear-spring VIV-based harvesters [123]. (Reproduced with permission from Ref. [123]. Copyright 2013 by AIP Publishing).

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Fig. 27

Schematic of the piezomagnetoelastic VIV harvester proposed by Naseer et al. [125]

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Fig. 28

Vortex-induced vibration-based harvester proposed by Song et al. [128]

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Fig. 29

Vortex-induced vibration-based harvester proposed by Hu et al. [129]

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Fig. 30

Drag assisted VIV-based harvester proposed by Arionfard and Nishi [130]. (Reproduced with permission from Ref. [130]. Copyright 2017 by Elsevier).

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Fig. 31

Power output of a piezoelectric harvester with different bluff bodies [131]

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Fig. 32

A schematic of a simplified model that captures the physical behavior of a flutter-based energy harvester. (Reproduced with permission from Ref. [133]. Copyright 2013 by Elsevier.

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Fig. 33

Variation of the real part of the eigenvalues with the wind speed. The parameters used in the simulations are based on the piezoaeroelastic MPG described in a prior work by Erturk et al. [158]. (Reproduced with permission from Ref. [133]. Copyright 2013 by Elsevier.)

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Fig. 34

Schematic of the flutter MPG proposed by Bryant and Garcia [136]

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Fig. 35

(a) Double plunge flutter energy harvester proposed by Wu et al. [148]; (b) a 3DOF flutter harvester with control surface studied by Dias et al. [149]; (c) arc-shaped harvester proposed by Zhao et al. [154]. (Part (c) reproduced with permission from Sensors and Actuators A: Physical, 236, 394–404. Copyright 2014 by Elsevier.)



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