A New Biomimicry Marine Current Turbine - Study of Hydrodynamic Performance

8/18/2019 A New Biomimicry Marine Current Turbine - Study of Hydrodynamic Performance

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2016,28(1):125-141DOI: 10.1016/S1001-6058(16)60614-5

A new biomimicry marine current turbine: Study of hydrodynamic performan-

ce and wake using software OpenFOAM*

Yung-Jeh CHU Department of Civil Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia,E-mail: [email protected]

(Received March 13, 2014, Revised August 20, 2015)

Abstract: Inspired by Dryobalanops aromatica seed, a new biomimicry marine current turbine is proposed. Hydrodynamic perfor-mance and wake properties are two key factors determining whether a new marine current turbine design is practical or not. Thus, astudy of hydrodynamic performance and wake of the proposed biomimicry turbine is conducted. The computational fluid dynamics(CFD) software, OpenFOAM is used to generate the required results for the mentioned study. The hydrodynamic performance andwake properties of the proposed biomimicry turbine is compared to two conventional turbines of Bahaj et al. and Pinon et al. re-spectively. The simulation results showed that the proposed biomimicry marine current turbine gives optimum power output with its

power coefficient, 0.376 P C ≈ at the tip speed ratio (TSR) of 1.5. Under the same boundary conditions, the maximum torque pro-

duced by the proposed biomimicry turbine at zero rotational speed is 38.71 Nm which is 1110% greater than the torque generated bythe turbine of Bahaj et al.. The recovery distance for the wake of the biomimicry turbine is predicted to be 10.6% shorter than that ofIFREMER-LOMC turbine. The above-mentioned results confirm the potential application of the proposed biomimicry marine curre-

nt turbine in the renewable energy industry.

Key words: marine current turbine, wake, biomimicry, computational fluid dynamics (CFD), OpenFOAM

Introduction0F

The hydrodynamic performance and wake properties are two key factors to determine whether a newmarine current turbine design is applicable in indust-ries or not. The torque and thrust generated by a rota-ting marine current turbine will determine its hydrody-namic performance during operation. On the otherhand, the wake property such as the wake recovery

distance is important in predicting the minimum spa-cing required between turbines in array. Thus, it is amust to conduct hydrodynamic performance and wakestudy through recognized methods in order to provethat the new marine current turbine design is worth in-vesting. There are a few recognized methods whichhave been used to measure or predict the hydrodyna-mic performance and wake properties of marine curre-nt turbines, among them are experiments and numeri-

* Biography: Yung-Jeh CHU (1987-), Male,Graduate Civil Engineer

cal simulations.There were few examples of successful experi-

ments conducted in measuring marine current turbinetorque, thrust and wake properties such as those stu-died in Refs.[1-10]. A typical experiment consists of amodel scaled turbine which immersed in a flume tankor a flow channel with supplies of inflow water inclose or open circuits. Sensors are used to measure the

torque and thrust on the turbine. The velocity at down-stream flow at various positions is usually measuredwith calibrated flow velocity measuring device suchas acoustic Doppler or laser Doppler velocimeter. Theexperimental results of the turbine wake can be reliable if the scaled model of the turbine is sufficientlylarge. In spite of the reliable results, many researcherschose to predict the hydrodynamic performance andturbine wake properties by using numerical simulatio-ns due to various restrictions on experiments such asexpensive set-up and long preparation time.

The CFD gains in popularity among researchers

as a tool for turbine research as shown in Refs.[11-15].Several CFD software such as ANSYS-FLUENT andOpenFOAM were available free or with affordable li-

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cense price. Due to the fast growth of technologynowadays most researchers are able to own at least ahigh performance workstation for research study. Thisenables accurate prediction of turbine wake propertiesto be obtained with shorter period of time compared to

experimental methods. However, most of the predi-cted simulation results still need to be validated by experimental results due to the errors induced by the nu-merical method itself such as truncation errors.

The objective of this study is to predict the hy-drodynamic performance and wake properties of a proposed biomimicry horizontal axis marine currentturbine by using the open sourceCFD software,OpenFOAM. The predicted hydrodynamic performan-ce of the biomimicry marine current turbine is compa-red to Ref.[4] while the predicted wake properties arecompared to Ref.[11]. The results from the compariso-

ns will give preliminary idea on the possible applica-tions of the proposed biomimicry marine current turbi-ne in renewable energy industry.

Fig.1 Snapshots of a Dryobalanops aromatica seeds found atGeology Faculty, University of Malaya (Note: Due to thenear distance of photographing, the objects nearer to thecamera appear to be larger. The 0.01 m grid size is onlyfor rough estimation)

1. Background of the proposed biomimicry marine

current turbine

The idea of mimicking the Dryobalanops aroma-tica seeds in turbine design was proposed by Chu du-ring his undergraduate, when Dryobalanops aromatica

seeds were found at the Geology Faculty in Universityof Malaya. The inspiration came when one of theDryobalanops aromatica seed was seen rotating stablyin the air during a visit to the Geology Faculty. Theunique shape of the wings of Dyrobalanops aromaticaseeds might suggest a solution in optimum turbine blade design. Thus, samples of Dryobalanops aromati-ca seeds were gathered, observed and photographedfor study use. Figure 1 shows the snapshots of aDryobalanops aromatica seeds found at Geology Fa-culty, University of Malaya.

Although the Dryobalanops aromatica seed uses

wind as the media of propagation, it is supposed thatits physical characteristics and flight mechanism can be applied in the design of marine current turbine.Thus, the biomimicry marine current turbine is propo-sed to have turbine blades similar to the shape of thewings of Dryobalanops aromatica seed, three-bladedand a downstream type turbine where the rotor is loca-ted behind the nacelle. Figure 2 further illustrates thecomponents of the proposed biomimicry turbine.

Fig.2 Sketch of the proposed 3-bladed biomimicry downstreamhorizontal axis turbine

2. Numerical simulationsTwo sets of numerical simulations were done in

terms of hydrodynamic performance and wake predi-ctions. For prediction of hydrodynamic performance,the geometrical properties of the proposed biomimicryturbine such as the number of blades, rotor size, hubsize and boundary conditions were totally made thesame as those of the turbine reported[4]. For wake pre-diction, all the geometrical properties of the proposed biomimicry turbine such as the number of blades,rotor size, hub size and boundary conditions were alsomade the same as those of the IFREMER-LOMC tur-

bine from Ref.[11]. The power coefficient, P C was setapproximately the same in wake simulation for thecases of IFREMER-LOMC and biomimicry turbine in


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order to check the differences of their wake propertieswhen the power output of both turbines is roughly thesame. Grid independence test was conducted to deter-mine the suitable mesh sizes for all simulation caseson account of the limiting available computational

power. The numerical simulation was continued withthe preferable set of mesh sizes and number of itera-tions. The discussion includes the predicted resultssuch as the torque, thrust, velocity line plots, pressureline plots, vorticity contour, velocity contour and par-ticle streamlines.

3. Computational hardware and softwareA workstation with processor Intel® Core™ i7-

4770K CPU @ 3.50 GHz×8, were used to run the si-mulations with Ubuntu 12.04 LTS as the operatingsystem. GetData and JavaFoil were used to generatethe coordinates required in turbine geometry mode-lling. GetData Graph Digitizer is a program for digiti-zing graphs and plots. JavaFoil is a relatively simple program, which uses several traditional methods forairfoil analysis. The geometry of the turbines was mo-delled by using SALOME. SALOME is an open-sou-rce software that provides a generic platform for Pre-and Post-Processing for numerical simulation. Themeshing and solving process was done in OpenFOAM.OpenFOAM is a free, open source CFD software pa-ckage developed by OpenCFD Ltd at ESI Group anddistributed by the OpenFOAM Foundation. ParaView

was used to view the simulation results. ParaView isan open-source, multi-platform data analysis andvisualization application.

Table 1 Turbine blade section properties from Ref.[4]

r /m /c R Pitch/ o 1 /t c−⋅ %

0.08 0.125 15.0 24.0

0.12 0.116 9.5 20.7

0.16 0.106 6.1 18.7

0.20 0.097 3.9 17.6

0.24 0.088 2.4 16.6

0.28 0.078 1.5 15.6

0.32 0.069 0.9 14.6

0.36 0.059 0.4 13.6

0.40 0.050 0 12.6

Note: r is the radius of local blade element, c is the blade

chord, R is the blade tip radius and t is the sectionthickness.

3.1 Bahaj et al.[4] turbine geometry modellingThe turbine from Ref.[4] consists of three turbine

blades. Its rotor diameter is 0.8 m, hub diameter is0.1 m and the turbine blades were developed from the profile shape of a NACA 63-8xx and with chord, thi-

ckness and pitch distribution presented in Table 1.

Fig.3 Conventional turbine geometry modelled according to thedetails available from Ref.[4]

Table 2 Blade section characteristics of the IFREMER-

LOMC turbine obtained from Ref.[11]

/r R /c R Pitch/ o

1

/t c−

⋅ %

0.13 0.06 29.57 80

0.15 0.06 29.57 100

0.16 0.06 29.57 100

0.20 0.15 25.63 36

0.24 0.25 22.15 21

0.29 0.24 19.30 21

0.33 0.23 16.97 22

0.37 0.21 15.05 22

0.42 0.20 13.46 22

0.46 0.19 12.12 22

0.50 0.18 10.98 23

0.55 0.17 10.01 23

0.59 0.17 9.18 22

0.63 0.16 8.45 22

0.68 0.15 7.82 22

0.72 0.15 7.26 21

0.76 0.14 6.77 21

0.81 0.14 6.34 20

0.85 0.13 5.95 19

0.89 0.13 5.61 19

0.94 0.12 5.29 18

0.98 0.12 5.01 18

1.00 0.07 4.87 25

Note: r is the radial distance measured from the rotationalaxis, R is the radius of turbine disk, c is the chordlength, t is the maximum thickness as a fraction of thechord.

The blade set angle is the angle at the tip of the blade, (i.e. the blade angles in Table 1 refer to a set


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angle of o0 )[4]. The blade is designed such that maxi-

mum power would be produced at a o5 set angle[4].

Thus o5 set angle of the turbine from Ref.[4] is usedin this study as a benchmark to determine the hydro-

dynamic performance of the proposed biomimicrymarine current turbine. The coordinates of the turbine blade surfaces in Ref.[4] were generated by usingJavaFoil according to the turbine blade section proper-ties in Table 1. The generated coordinates of the turbi-ne blade surfaces in Ref.[4] were then exported toSALOME for turbine geometry modelling. The mode-lled turbine as that of Ref.[4] is shown in Fig.3.

Fig.4 The modelled IFREMER-LOMC turbine geometry usingSALOME

Fig.5 Photographs showing outlines (light grey) of a wing ofDryobalanops aromatica seed used in biomimicry turbine

blade modelling. The left side of the photo shows conca-ve surface while the right side shows the side view of awing of Dryobalanops aromatica seed

Fig.6 The modelled biomimicry turbine geometries inspired byDryobalanops aromatica seed

Fig.7 Definition of rake, pitch and skew angles of the proposed biomimicry turbine blade (viewed from the top of turbine)in this study

Fig.8 Power coefficient graph of the proposed biomimicry turbine with different combinations of turbine blades pitch

and skew angles e.g., 15p30s means o15 in pitch ando30 in skew

Fig.9 Power coefficient graph (zoomed in for the sake of clari-fication) of the proposed biomimicry turbine with differe-nt combinations of turbine blades pitch and skew angles

e.g. 15p30s means o15 in pitch and o30 in skew


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Table 3 Grid independence test result for Ref.[4] turbine case witho5 set angle, TSR = 2 and =1.73m/sU ∞

Number of cells Average node interval sizeon blades surfaces/m

Number of iterations P

C T

C

262 754 0.0015

500 0.0611 0.2721

5 000 0.0611 0.2722

10 000 0.0611 0.2722

655 362 0.0010

500 0.0591 0.2680

5 000 0.0591 0.2683

10 000 0.0590 0.2684

1 304 043 0.0008

500 0.0573 0.2649

5 000 0.0574 0.2658

10 000 0.0575 0.2660

Table 4 Grid independence test result for biomimicry turbine case with rake angle o40 , pitch angle o15 , skew angle o30 ,

TSR =1 and =1.73m/sU ∞

Number of cells Average node interval sizeon blades surfaces /m

Number of iterations P C T C

265 542 0.0015

500 0.2715 0.8160

5 000 0.2729 0.8364

10 000 0.2728 0.8351

680 424 0.0010

500 0.2735 0.8175

5 000 0.2730 0.832110 000 0.2747 0.8396

1 373 305 0.0008

500 0.2744 0.8112

5 000 0.2752 0.8384

10 000 0.2747 0.8370

3.2 IFREMER-LOMC turbine geometry modellingThe IFREMER-LOMC turbine geometry from

Ref.[11] consists of three turbine blades, 0.700 mrotor diameter, 0.046 m hub radius and 0.720 m hublength. The turbine blades were developed from the

profile shape details as shown in Table 2.The background of the IFREMER-LOMC turbi-

ne is as shown in the following quotes extracted fromRef.[11]:

“The second set of blades used for validation purposes was first designed by tidal generation limited(TGL) and experimentally tested in the IFREMERflume tank of Boulogne-sur-Mer (France). However,this set of blades, presented in Maganga et al., is pa-tented so a similar and open set of blades was developed for experimental validation at IFREMER and nu-merical trial at LOMC-Le Havre University (France).

In the present paper, this last open blades configura-tion will be named as the IFREMERLOMC configura-tion. The turbine blades are designed from a

NACA63418 profile.”JavaFoil and SALOME were used to produce the

geometry of the IFREMER-LOMC turbine. The mo-delled geometry was then exported to OpenFOAM forsimulation. Figure 4 shows the 3-D view of

IFREMER-LOMC turbine geometry modelled in thisstudy.

3.3 Biomimicry turbine blade geometry modellingThe photo of a wing of Dryobalanops aromatica

seed were used to generate the required blade surfacecoordinates for the mentioned geometry modelling.The coordinates of the outlines of the wing ofDryobalanops aromatica seed is generated by usingGetData. The generated coordinates were then expo-rted to SALOME for geometry modelling. In order tohave a fair comparison with the simulation cases of

Ref.[4] and IFREMER-LOMC turbine, the rotor dia-meter, hub and the number of turbine blades of thetwo modelled biomimicry marine current turbines


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were made the same as those in Refs.[4] and [11]. Thekey difference between the biomimicry turbine andthe turbine from Refs.[4] and [11] is the shape of theturbine blades. Figure 5 shows the photos of a wing ofDryobalanops aromatica seed while Fig.6 shows the

two modelled biomimicry marine current turbines forhydrodynamic performance and wake simulations.

3.4 Optimum biomimicry turbine geometry test The definition of rake, pitch and skew angles of

the biomimicry turbine blade are as shown in Fig.7.

The rake angle was fixed to o40 while the skew and pitch of the biomimicry turbine blades were altered inorder to see which combination will give optimum power output. Lower mesh numbers (each case around250 000) were applied in this test.

Simulation results from eight different combina-

tions of pitch and skew angles of the biomimicry turbine blade in the optimum turbine geometry test are asshown in Fig.8 and Fig.9. From the results shown, the

combinations of o15 pitch and o30 skew gives thehighest maximum power coefficient,

P C which is

around 3.8 among other combinations. Thus, it was

decided that this combinations of o15 pitch and o30 skew is to be implemented into the biomimicry turbi-ne geometry for the hydrodynamic performance comparisons.

3.5 Boundary and initial conditionsFor the simulation of hydrodynamic performance,

the free stream velocity, =1.73m /sU ∞ with initial

turbulence intensity = 5% were applied throughout themesh domain of all the turbine of Ref.[4] and biomi-micry turbine. The rotational speed of the rotor wasaltered according to the specific tip speed ratio (TSR)for each simulation case. Standard -k ε wall functionwas applied at the turbine blades surfaces.

On the other hand, the free stream velocity,= 0.8 m / sU ∞ with initial turbulence intensity = 5%

were applied throughout the mesh domain of both the

IFREMER-LOMC turbine and biomimicry turbinewake simulation cases. Standard -k ε wall functionwas also applied at the turbine blades surfaces of bothsimulation cases. Several trials with different rotatio-nal speed and tip speed ratio of rotor were done for both simulation cases to obtain the same predicted power coefficient,

P C while it was not being conce-

rned for the case of thrust coefficient, T C in this study.

Through trial and errors, it was found that the opti-mum predicted power coefficient,

P C of both the

IFREMER-LOMC turbine and biomimicry turbine

cases were very near, 0.37 and 0.38, respectively.Thus, the wake properties of the IFREMER-LOMCturbine and biomimicry turbine simulation cases with

optimum TSR 3.67 and TSR 1.5 respectively werecompared.

The predicted power coefficient, P C and thrust

CoefficientT C in this study were calculated with

Eqs.(1)-(3).

3 2

2= P

QC

U R

Ω

ρ ∞ π

(1)

2 2

2=T

T C

U R ρ ∞ π

(2)

= R

U

Ω λ

∞

(3)

where P C is the power coefficient, T C is the thrustcoefficient, λ is the tip speed ratio, Q is the torque,

Ω is the angular speed, ρ is the density of fluid, U ∞

is the free stream velocity, R is the radius of rotorand T is the thrust.

Fig.10 Mesh domain slice sections

3.6 Solver, libraries and turbulence modelAll the simulation cases in this study were solved

by using the OpenFOAM solver namedMRFSimpleFOAM. MRFSimpleFOAM is a steady-state solver for incompressible, turbulent flow of flui-ds with multiple reference frame (MRF) regions. The


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Table 5 Mesh properties of simulation case for Biomimicry and IFREMER-LOMC turbine

Number of mesh cells Blade surface mesh size/m Rotor mesh size/m Stator mesh size/m

IFREMER-LOMCturbine case

525 982 0.0031 0.0250 0.050

1 610 174 0.0020 0.0165 0.033

3 667 938 0.0015 0.0125 0.025

Biomimicryturbine case

592 672 0.0030 0.0250 0.050

1 765 874 0.0021 0.0165 0.033

3 937 105 0.0016 0.0125 0.025

SST -k ω turbulence model was adopted for the si-mulations in this study. The torque and thrust of theturbine was calculated by the tool from a post-proce-ssing library named “forces”. The “forces” post-proce-

ssing library provides tools for post-processing force/lift/drag data with function objects.

3.7 Grid independence test for hydrodynamic perfor-mance simulation caseGrid independence test was conducted for the

Ref.[4] and biomimicry turbine case to ensure themesh quality is enough to achieve accurate results. Di-fferent number of cells and number of iterations wereapplied in the test and the results are as shown inTable 3 and Table 4.

From the result of the grid independence test, the

P C

and

T C

values converged at 10 000 iterations and1 304 042 mesh cells for the turbine of Ref.[4]. Forthe biomimicry turbine, the

P C and T C values con-

verged at 10 000 iterations and 1 373 305 mesh cells.Thus, all the hydrodynamic performance simulationswere run in 10 000 iterations and the mesh with1 304 043 cells is chosen for simulations of turbinefrom Ref.[4] while the mesh with 1 373 305 cells ischosen for the biomimicry turbine simulations. Figure10 shows the mesh domain slice sections for the simu-lation cases of Ref.[4] and biomimicry turbine.

The quantitative uncertainties for the grids were

estimated using the factor of safety method and theyare referred to [16-19]. The uncertainties of P C and

T C were 2.5%S and 15.7%S (where %S is per-

centage of fine grid solution) of the 1 304 042 meshcells solution for the turbine of Ref.[4] while it is5.1%S and 10.2%S of the 1 373 305 mesh cells so-lution respectively for the biomimicry turbine.

3.8 Grid independence test for wake simulation caseGrid independence test was also conducted for

both IFREMER-LOMC turbine from Ref.[11] and biomimicry turbine to ensure good mesh quality. Si-

mulation of cases with different mesh cell numbers

were run in the test and their mesh properties are asshown in Table 5.

The difference in mesh size and number of cells between the IFREMER-LOMC turbine and Biomimi-

cry turbine were adjusted to be as small as possible toavoid different influence due to different grid size.The velocity distribution located at a distance of 1.2 D (0.84 m) from the origin was adopted for the test. Theresults from the test show that the influence of the gridsizes was of minimum when the number of cells rea-ches 3 667 938 for IFREMER-LOMC turbine while itwas 3 937 105 for biomimicry turbine. The optimumnumber of iterations for the best results is about10 000. The velocity distribution plots were as shownin Fig.11 while the slice sections of the mesh domainsare presented in Fig.12 and Fig.13.

Similar to grid independence test for hydrodyna-mic performance, the uncertainties for the grids wereestimated using the factor of safety method. The un-certainty of the axial velocity at lateral distance = 0 is 12.4%S of the 366 7938 mesh cells solution forIFREMER-LOMC turbine while it is 14.2%S of the3 937 105 mesh cells solution for biomimicry turbine.

4. Results and discussionFor the case of hydrodynamic performance, dis-

cussion is focused on the predicted hydrodynamic tor-que and thrust from the simulation results for the tur-

bine of Ref.[4] and biomimicry marine current turbine.Comparisons on power coefficient, P C and thrust coe-

fficient, T C for each simulated turbines were also pre-

sented and discussed in this section. For the case ofwake predictions, several aspects of the turbine wake properties of the IFREMER-LOMC turbine and the proposed biomimicry turbine were discussed in detail.The discussed aspects were the velocity distribution,vorticity, pressure distribution, wake recovery dista-nce and the particle streamlines from the predicted re-sults. Through the comparisons of the results fromthese aspects, the feasibility of the proposed biomimi-

cry turbine to be adopted in turbine farm design can


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Fig.11 Velocity line plots at distance of 1.2 D from origin withdifferent mesh numbers. Velocity line plots at distanceof 1.2 D from origin with different number of iterations

be predicted. Table 6 shows the summary of the con-ditions and predicted results for the wake simulation

of the IFREMER-LOMC turbine and biomimicry turbine.

4.1 Torque and thrust predictionThe hydrodynamic performance of the proposed

biomimicry marine current turbine outweighs the turbine of Ref.[4] in terms of torque. Referred to Table 7,the hydrodynamic torque produced by the biomimicryturbine is greater than that of Ref.[4] from TSR = 0 to TSR = 2.5 . The predicted maximum torque produ-ced by the proposed biomimicry marine current turbi-ne at zero rotational speed is 38.71 Nm which is1 110% greater than the torque generated by the turbi-ne of Ref.[4]. The high torque generated by the biomi-micry turbine can overcome resisting torque (e.g. cau-sed by friction) from the nacelle effectively and thusavoids rotor jamming problems especially during ini-

tial stage when the turbine starts to rotate. Table 7shows the hydrodynamic torque comparison betweenturbine of Ref.[4] and biomimicry turbine.

The high thrust produced by the biomimicry turbine as shown in Table 7 is detrimental to the turbine blade root due to the induced bending moment. Therequired rigidity and elastic properties of the turbine blade will be determined by the thrust produced by themarine current turbine during its operation. Higher ge-nerated thrust will lead to more amount of or expensi-ve materials needed to strengthen the turbine bladeroot. However, the blade root bending moment might

be able to be alleviated by introducing flexible turbine blade. Further study will be conducted in the future toinvestigate the efficiency of flexible turbine blade inrelieving blade root bending moment. Despite the blade rigidity issue, the thrust produced by the biomi-micry turbine at optimum TSR, TSR =1.5 is only13.24% greater than the thrust produced by the turbineof Ref.[4] at its optimum Tip Speed Ratio, TSR = 6.0 .This extra 13.24% of thrust can be overcome by stre-ngthening the blade root with stronger material and proper reinforcement. The suitable blade thicknessand materials to strengthen the biomimicry blade will

also be investigated in future study.The power coefficients, P C predicted in this

study show that the biomimicry marine current turbineoperates at lower, TSR. This means that with the samerotor size and a given free stream velocity, the biomi-micry turbine will rotates slower than conventionalturbine e.g. when compared to the turbine of Ref.[4].This slow operating rotational speed makes the biomi-micry marine current turbine environmental friendlyas the collision risk is expected to be low compared toother conventional marine current turbines. Figure 14and Fig.15 show the predicted power coefficient and

thrust coefficient with the results adopted fromRef.[4].


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Table 6 Summary of conditions and predicted results of wake simulation for IFREMER-LOMC and biomimicry turbine

Incomingflow

velocity,

U ∞ /ms

−1

Rotordiameter/

m

Numberof

blades

Hubradius/

m

Hublength/

m

OptimumTSR

Rotationalspeed/rad∙s

−1

Predictedtorque/ Nm

Predictedthrust/N

P C T C

IFREMER-LOMC

0.8 0.7 3 0.046 0.720 3.670 8.390 4.360 82.980 0.370 0.670

Biomi-micry 0.8 0.7 3 0.046 0.720 1.500 3.430 10.920 125.450 0.380 1.018

Table 7 Hydrodynamic torque comparison between the turbine of Ref.[4] and biomimicry turbine

Bahaj et al.[4] turbine case Biomimicry turbine case

TSRTorque/

NmThrust/

NTSR

Torque/ Nm

Thrust/ N

0 3.20 95.41 0 38.71 373.72

0.5 3.28 105.20 0.5 43.03 418.18

1.0 4.23 128.87 1.0 82.67 629.61

2.0 8.66 200.15 1.5 75.39 767.99

4.0 25.59 448.31 2.0 52.14 840.54

6.0 25.99 678.18 2.5 33.13 972.73

8.0 19.55 798.37 3.0 1.48 1 004.85

10.0 11.93 870.14 3.5 −34.41 1 039.75

4.0 −74.71 1 079.62

Fig.14 Power coefficient graph of the turbines resulted from ca-vitation tunnel, towing tank, SERG-Tidal, GH-TidalBladed and OpenFOAM simulations. The cavitation tu-nnel, towing tank, SERG-Tidal and GH-Tidal Bladedresults were adopted from Ref.[4]

of this biomimicry marine current turbine with respectto the stated limitation will be discussed in futurestudy.

Validation of the OpenFOAM predicted P C and

T C were done by referring to the experimental results

from Ref.[4] and also Ref.[11]. The average compari-son error of the OpenFOAM predicted P C and T C

with Ref.[4] turbine is 20.63% E − and 10.65% E −

Fig.15 Thrust coefficient graph of the turbines resulted fromcavitation tunnel, towing tank, SERG-Tidal, GH-TidalBladed and OpenFOAM simulations. The cavitation tu-nnel, towing tank, SERG-Tidal and GH-Tidal Bladedresults were adopted from Ref.[4]

(where % E is percentage of experimental data) whileit is 15.38% E − and 17.59% E − respectively for thecase of IFREMER-LOMC turbine. These large avera-ge comparison error may be due to the limitations ofthe implemented turbulence model or solver in predi-cting accurate hydrodynamic forces especially in high

pressure gradient region e.g. blade surfaces and nearwake region. The cause of this large average compari-son error will be studied in future by comparing the


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results from implementing different turbulence modelsand solvers to simulation of the turbine of Ref.[4] andIFREMER-LOMC marine current turbine e.g. otherLow-Reynolds turbulence model with transient solver.

Fig.16 Power coefficient graph of the turbines resulted fromexperiment, particle method and OpenFOAM simulatio-ns. The IFREMER-LOMC experiment and particle me-thod results were adopted from Ref.[11]. ε representssmoothing parameter in particle method prediction byRef.[11].

Fig.17 Thrust coefficient graph of the turbines resulted fromexperiment, particle method and OpenFOAM simulatio-ns. The IFREMER-LOMC experiment and particle me-thod results were adopted from Ref.[11]

4.2 Velocity, vorticity and pressure distribution

The axial velocity contour plots and velocity line plots of the wake of IFREMER-LOMC turbine and biomimicry turbine were discussed in this study. Theaxial velocity contour plots show no significant diffe-rence of the turbine wake pattern at the far wake re-gion while the degree of fluctuations of axial velocityis very much different at the near wake region. Thenear wake region is defined as the wake region withindistances of 4 D from origin while the far wake regionis farther than 4 D away in the downstream directionaccording to Ref.[11]. Figure 18 shows the simulatedvelocity contour plots along the downstream direction

for the IFREMER-LOMC turbine and biomimicry turbine.

To go in depth on the turbine wake properties,

the velocity line plots are discussed. This discussionwill focus on the difference of OpenFOAM results onturbine wake between the IFREMER-LOMC turbineand biomimicry turbine. The purpose of including theexperimental and particle method results from Ref.[11]

is to validate the results for IFREMER-LOMC turbine predicted by OpenFOAM. Since the velocity line plotsof the IFREMER-LOMC turbine predicted byOpenFOAM lies within the ranges of the experimentaland particle method results from Ref.[11] as shown inFigure 19 and Figure 20, the validation is considereddone for this study. Figure 19 shows the near wakewhile Figure 20 shows the far wake of the axial velo-city distribution line plots for IFREMER-LOMC turbine and Biomimicry turbine.

For the case of near wake, the velocity distribu-tion of the biomimicry turbine wake predicted by

OpenFOAM shows lower axial velocity values at theaxis of rotation, / = 0 z D compared to IFREMER-LOMC turbine. This low axial velocity suggests thatthe larger blade area of the biomimicry turbine captu-res more incoming flow near the hub region comparedto IFREMER-LOMC turbine. This is different at farwake region where the axial velocity on the axis ofrotation of the biomimicry turbine wake is highercompared to IFREMER-LOMC turbine. This mightmeans that the wake recovery of the biomimicry turbi-ne wake is shorter than the IFREMER-LOMC turbinewake. The axial velocity distribution for the biomimi-

cry turbine and IFREMER-LOMC turbine were of nomuch difference at the wake region outside the rotorarea, for / 0.5 z D > and / 0.5 z D < − . This suggeststhat the wake expansion for the biomimicry turbinewake is the same as the IFREMER-LOMC turbinewake throughout the downstream direction. This resultalso implies that the spacing of a biomimicry turbinefarm in lateral can be the same as a turbine farm fromIFREMER-LOMC turbines.

There are significant differences observed in thevorticity contour plots of the predicted wake ofIFREMER-LOMC turbine and biomimicry turbine.More vortices formed in a turbine wake means moretranslational flow being converted to local rotationalflow. If more translational flow is being converted tolocal rotational flow, then there will be less energy leftfor extraction in the downstream wake. For the case ofIFREMER-LOMC turbine wake, the flow with highvorticity magnitude (Vorticity magnitude 1≈ ) is distri- buted further downstream compared to the biomimi-cry turbine wake. The high vorticity regions are distri- buted at the tip of the IFREMER-LOMC turbine andalso behind its hub. The biomimicry turbine wake vor-ticity is observed to be concentrated nearer to the turbine. These differences further support that the biomi-

micry turbine wake recovery distance is shorter compared to IFREMER-LOMC turbine wake. Figure 21


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Fig.18 Velocity contour plots

Fig.19 Velocity line plots showing axial velocity distribution at different locations in near wake at downstream direction for

IFREMER-LOMC and Biomimicry turbine cases from this study and Ref.[11]. Note: The letter D denotes measurement ofdistance in diameters of rotor, in this case 1.0 D is 0.7 m. e.g. 1.2 D means 1.2 times diameter of rotor measured fromorigin. The lateral bars for the experimental data represent the standard deviation around the mean velocity value


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Fig.20 Velocity line plots showing axial velocity distribution at different locations in far wake for IFREMER-LOMC turbine andBiomimicry turbine from this study and Ref.[11]

Fig.21 Vorticity contour plots of simulation


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re at the axial region ( = 0) z . This reduction of pre-

ssure indicates that the flow is disturbed and sloweddown by the rotating turbine. It is observed that thedip of the pressure distribution of the biomimicry turbine at the near wake is lower than the IFREMER-LOMC turbine (at =1.2 y D , 2.0 D , 3.0 D and 4.0 D ).

The dip of the pressure distribution of the biomimicryturbine wake becomes higher than the dip of the pre-ssure distribution of the IFREMER-LOMC turbinewake further downstream from the location at = y

6.0 D . This observation also strengthens the idea thatthe wake recovery distance for the biomimicry turbineis shorter than the wake recovery distance ofIFREMER-LOMC turbine wake. Figure 22 shows the pressure distribution plot of the IFREMER-LOMCand biomimicry turbine at near wake while Fig.23

shows the pressure distribution plot of the IFREMER-LOMC and biomimicry turbine at far wake.Validation of the OpenFOAM predicted turbine

wake axial velocity was done by referring to the expe-rimental results from Ref.[11]. The average compari-son error of the OpenFOAM predicted axial velocitieswith Ref.[11] turbine ranges from 8.83% E − to

3.30% E − with a decreasing magnitude of % E towa-rds downstream direction.

Fig.24 Mean axial velocity deficit against downstream distancegraph for experimental and numerical results on thewake of IFREMER-LOMC turbine and biomimicrytidal turbine

4.3 Wake recovery distancesThe mean axial velocity deficits along the down-

stream direction of the turbine wake were calculated by using the integrated axial velocity deficit equationsfrom Ref.[11]. Equations (4)-(6) as shown below werethe related equation used in obtaining the mean velo-city deficits.

*

**2

1( ) = ( , )d

R

Ru y z u y z y

R −∫ (4)

( ) = 1 00[1 ( )] y u yγ − (5)

* = + R R r δ (6)

where ( )u y is the mean axial velocity, R∗

is the ra-dius of the disc representing the turbine’s area of in-fluence, z is the lateral distance, ( , )u y z is the axial

velocity, ( ) yγ is the mean axial velocity deficit, R

is the radius of the turbine disc and r δ is the assumedradial increment due to turbine’s area of influence.

Pinon et al.[11] took 0.05 m = 0.14r Rδ ≈ . This

enlarged the integration interval to the two nearest experimental measurement nodes outside the rotor. Thewhole velocity deficit was taken into account in thisway including the velocity deficit of the biomimicry

turbine wake. Figure 24 shows the mean axial velocitydeficit graphs between wakes IFREMER-LOMC turbine and biomimicry turbine.

Fig.25 Predicted wake recovery distance of IFREMER-LOMCturbine and biomimicry turbine simulated byOpenFOAM on the mean axial velocity deficit againstdownstream distance graph. It is about 16.0 D (11.21 m) for biomimicry turbine while it is about17.9 D (12.54 m) for IFREMER-LOMC turbine

Fig.26 Particle streamlines at zero rotational speed (Note: Leftside image shows back view while right side imageshows side view of the mentioned particles streamlines)


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(3) The power coefficients predicted in this studyshow that the biomimicry marine current turbine ope-rates at lower TSR. This low operating rotationalspeed makes the biomimicry marine current turbineenvironmental friendly as the collision risk is expected

to be relatively low compared to other conventionalmarine current turbines.

(4) The near wake region of the biomimicry ma-rine current turbine showed significant reduction inaxial velocity. This result may indicate the effective-ness in capturing incoming flow due to larger bladearea of the proposed biomimicry turbine. The far wakeregion of the biomimicry marine current turbine sho-wed that the expansion of the wake is not much diffe-rent from the IFREMER-LOMC turbine wake. Thisresult suggests that the spacing of the biomimicry turbine farm in lateral can be the same compared to a tur-

bine farm from IFREMER-LOMC turbines.(5) The predicted wake recovery distances isabout 16.0 D (11.21 m) for biomimicry turbine casewhile it is about 17.9 D (12.54 m) for IFREMER-LOMC turbine. This made the wake recovery distanceof the proposed biomimicry turbine 10.6% shorterthan that of IFREMER-LOMC turbine. This shortwake recovery distance suggests that the performanceof a turbine farm will be improved by implementingthe proposed biomimicry turbine as more turbines can be included in a specific area.

(6) The predicted water flow at the wakes of bio-

mimicry turbine and IFREMER-LOMC turbine is he-lical. The shorter pitch of the helix water particle path-way at biomimicry turbine wake suggest that the bio-mimicry turbine is able to convert the translationalenergy into rotational energy effectively despite thelow operating rotational speed applied.

Experiments will be conducted in future study tofurther validate the predicted results. Through thesestudies, it is hope that the proposal of this biomimicrymarine current turbine will be able to bring advance-ment in marine current turbine industries.

AcknowledgementsThe author wish to extend his gratitude to Uni-

versity of Malaya for the facilities and services provi-ded in supporting this study and also the effort in pre-serving the Dryobalanops aromatica trees in the cam- pus.

References

[1] MCADAM R. A., HOULSBY G. T. and OLDFIELD M. L.G. Experimental measurements of the hydrodynamic per-formance and structural loading of the transverse horizo-ntal axis water turbine: Part 2[J]. Renewable Energy,

2013, 59(6): 141-149.[2] MCADAM R. A., HOULSBY G. T. and OLDFIELD M. L.G. Experimental measurements of the hydrodynamic per-

formance and structural loading of the transverse horizo-ntal axis water turbine: Part 3[J]. Renewable Energy, 2013, 59(6): 82-91.

[3] BAHAJ A. S., MOLLAND A. F. and CHAPLIN J. R. et al.Power and thrust measurements of marine current turbinesunder various hydrodynamic flow conditions in a cavita-tion tunnel and a towing tank, Renew[J]. Renewable Ene-rgy, 2007, 32(3): 407-426.

[4] BAHAJ A. S., BATTEN W. M. J. and MCCANN G. Ex- perimental verifications of numerical predictions for thehydrodynamic performance of horizontal axis marine cu-rrent turbines[J]. Renewable Energy, 2007, 32(15): 2479-2490.

[5] MYERS L., BAHAJ A. S. Wake studies of a 1/30th scalehorizontal axis marine current turbine[J]. Ocean Enginee-ring, 2007, 34(5-6): 758-762.

[6] MYCEK P., GAURIER B. and GERMAIN G. et al. Ex- perimental study of the turbulence intensity effects on ma-rine current turbines behaviour. Part I: One single turbi-ne[J]. Renewable Energy, 2014, 68(7): 729-746.

[7] MYCEK P., GAURIER B. and GERMAIN G. et al. Ex- perimental study of the turbulence intensity effects on ma-rine current turbines behaviour. Part II: Two interactingturbines[J]. Renewable Energy, 2014, 68(7): 876-892.

[8] MYCEK P., GAURIER B. and GERMAIN G. et al. Nu-merical and experimental study of the interaction betweentwo marine current turbines[J]. International Journal ofMarine Energy, 2013, 1: 70-83.

[9] TEDDS S. C., OWEN I. and POOLE R. J. Near-wakecharacteristics of a model horizontal axis tidal stream turbine[J]. Renewable Energy, 2014, 63(1): 222-235.

[10] MAGANGA F., GERMAIN G. and KING J. et al. Experi-mental characterisation of flow effects on marine currentturbine behaviour and on its wake properties[J]. Iet Re-

newable Power Generation, 2010, 4(6): 498-509.[11] PINON G., MYCEK P. and GERMAIN G. et al. Numeri-cal simulation of the wake of marine current turbines witha particle method[J]. Renewable Energy, 2012, 46(5):111-126.

[12] ZHAO Guang, YANG Ran-sheng and LIU Yan et al. Hy-drodynamic performance of a vertical-axis tidal-currentturbine with different preset angles of attack[J]. Journalof Hydrodynamics, 2013, 25(2): 280-287.

[13] WANG Ji-feng, PIECHMA Janusz and MÜLLER NorbertA novel design of composite water turbine using CFD[J].Journal of Hydrodynamics, 2012, 24(1): 11-16.

[14] MAGANGA F., PINON G. and GERMAIN G. et al. Nu-merical simulation of the wake of marine current turbineswith a particle method (congress)[J]. World RenewableEnergy Congress X 2008. Glasgow, UK, 2008.

[15] KANG S., BORAZJANI I. and COLBY J. A. et al. Nume-rical simulation of 3D flow past a real-life marine hydro-kinetic turbine[J]. Advances in Water Resources, 2012,39: 33-43.

[16] OBERKAMPF W. L., ROY C. J. Verification and vali-dation in scientific computing[M]. New York, USA:Cambridge University Press, 2010.

[17] ROACHE P. J. Verification of codes and calculations[J].AIAA Journal, 1998, 36(5): 696-702.

[18] XING T., STERN F. Closure to “Discussion of ‘Factors ofsafety for Richardson extrapolation’ˮ[J]. Journal ofFluids Engineering, 2011, 133(11): 115501.

[19] XING T., STERN F. Factors of safety for Richardson ex-

trapolation[J]. Journal of Fluids Engineering, 2010,132(6): 061403.

A New Biomimicry Marine Current Turbine - Study of Hydrodynamic Performance

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