A biomimetic wind turbine inspired by Dryobalanops aromatica seed: numerical prediction of rigid rotor blade performance with OpenFOAM\(^{\circledR}\).

*(English)*Zbl 1390.76413Summary: This paper presents the performance study of a rigid biomimetic horizontal axis wind turbine (HAWT) rotor blade inspired by Dryobalanops aromatica seed with open source computational fluid dynamics (CFD) software, OpenFOAM\(^{\circledR}\). The power coefficient, \(C_{P}\), thrust coefficient, \(C_{T}\) and blade root bending stresses of the proposed biomimetic wind turbine were predicted and compared to a tapered and twisted blades wind turbine from P.-Å. Krogstad and J. A. Lund, “An experimental and numerical study of the performance of a model turbine”, Wind Energy 15, No. 3, 443–457 (2011; doi:10.1002/we.482)]. The simulation results show that the proposed biomimetic wind turbine has fair maximum \(C_{P}\) which is 0.386 at tip speed ratio (TSR) of 1.5 in free stream velocity, \(U_{\infty}\) of 10 m/s. The proposed biomimetic wind turbine is expected to have better self-starting ability as its starting torque at \(TSR=0\), is 772% higher than [loc. cit.] wind turbine. The proposed biomimetic wind turbine is also expected to work in low wind speed condition due to its ability to generate higher torque during rotation. The preconing of the proposed biomimetic wind turbine blades enable the utilisation of centrifugal forces induced from rotation to reduce flapwise bending stresses. The performance of the scaled biomimetic wind turbine which have similar solidity as [loc. cit.] wind turbine was also tested and it was able to exhibit the features of the original biomimetic wind turbine. This preliminary study will give insight on the potentials of this newly proposed biomimetic wind turbine in the wind power industry.

##### MSC:

76M12 | Finite volume methods applied to problems in fluid mechanics |

76U05 | General theory of rotating fluids |

65M08 | Finite volume methods for initial value and initial-boundary value problems involving PDEs |

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\textit{Y.-J. Chu} and \textit{W.-T. Chong}, Comput. Fluids 159, 295--315 (2017; Zbl 1390.76413)

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