Stability and optimal forcing analysis of a wind turbine wake: Comparison with POD

Cillis, Giovanni De; Cherubini, Stefania; Semeraro, Onofrio; Leonardi, Stefano; Palma, P. De

doi:10.1016/j.renene.2021.09.025

Cited by 14 publications

(4 citation statements)

References 48 publications

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“…Spatial Fourier transform of these modes allows one to find a dominant streamwise wavenumbers in the range α ≈ 4 − 5, which are consistent with the dominant streamwise wavenumbers recovered by local stability analyses of the wake flow behind low-Reynolds number wind turbines [39,40]. Notice that, for γ = 40000, four out of the five selected modes are characterized by temporal and spatial wavenumbers in this range, suggesting that these large-scale oscillations have a strong dynamical relevance for the considered flow.…”

Section: Resultssupporting

confidence: 70%

Dynamic-mode-decomposition of the wake of the NREL-5MW wind turbine impinged by a laminar inflow

Cillis

Semeraro

Leonardi³

et al. 2022

Renewable Energy

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Section: Resultssupporting

confidence: 70%

Dynamic-mode-decomposition of the wake of the NREL-5MW wind turbine impinged by a laminar inflow

Cillis

Semeraro

Leonardi³

et al. 2022

Renewable Energy

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“…The multiple-resolvent composition can be considered as a deep resolvent that includes more desired physics. Planned future work will focus on the development of the multiple-resolvent composition to successive approximation to space-time statistics in turbulent flows, such as wall-bounded turbulence (Jiménez 2018;Wang, Wang & He 2018;Wang & Gao 2021), turbulent jets (Jordan & Colonius 2013;Schmidt et al 2018) and wakes (De Cillis et al 2022;Dong et al 2022).…”

Section: Conclusion and Remarksmentioning

confidence: 99%

Composition of resolvents enhanced by random sweeping for large-scale structures in turbulent channel flows

He²

2023

J. Fluid Mech.

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Composite sweeping-enhanced resolvents, referred to as the ${\boldsymbol {R}}_s^2$ model, are proposed to predict the space–time statistics of large-scale structures in turbulent channel flows. This model incorporates two key mechanisms: (i) eddy damping is introduced to represent random sweeping decorrelation caused by nonlinear forcing, leading to a sweeping-enhanced resolvent ${{\boldsymbol {R}}_s}$ ; and (ii) the sweeping-enhanced resolvent ${{\boldsymbol {R}}_s}$ is composited into its iterations ${\boldsymbol {R}}_s^2$ to yield non-zero Taylor time microscales. The resulting ${\boldsymbol {R}}_s^2$ model can correctly predict the frequency spectra and two-point cross-spectra of large-scale structures. This model is compared numerically with eddy-viscosity-enhanced resolvent models. The latter are designed to represent energy transfer instead for time decorrelation, and thus underpredict the characteristic decay time scales. The ${\boldsymbol {R}}_s^2$ model correctly yields the characteristic decay time scales in turbulent channel flows.

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“…Proper Orthogonal Decomposition (POD) is a useful tool for analysing experimental or numerical datasets from a statistical point of view, since it provides an energetically optimal orthogonal basis for decomposing the data. In the case under consideration, it provides the most energetic coherent structures characterising the flow field q(x, t) [32].…”

Section: Proper Orthogonal Decompositionmentioning

confidence: 99%

How incoming turbulence affects wake recovery of an NREL-5MW wind turbine

Cherubini

Cillis²,

Semeraro

et al. 2022

J. Phys.: Conf. Ser.

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The present work aims at investigating the effect of inflow turbulence on the wake recovery of the NREL-5MW reference wind turbine. The wake produced by a utility-scale wind turbine invested by both a laminar uniform inflow and a turbulent flow, is analyzed by means of proper-orthogonal decomposition (POD). The considered turbine is the NREL-5MW at tip-speed ratio λ = 7 and a diameter-based Reynolds number of the order 108. The flow is simulated through Large Eddy Simulation, where the forces exerted by the blades are modeled using the Actuator Line Method, whereas tower and nacelle are modeled employing the immersed boundary method. The main flow structures identified by modal decomposition in both of the considered cases are compared, and some differences emerge, which can be of great importance for the formulation of a reduced-order model. Among the most energetic modes, a high-frequency mode directly related to the tip vortices is found only in the flow case with laminar inflow. In the presence of inflow turbulence, the most energetic modes are all composed by large-scale low-frequency structures filling the whole domain. We evaluate the contribution of each POD mode to wake recovery reconstructing the total flux of mean kinetic energy due to turbulent fluctuations on a closed surface enclosing the wake of the wind turbine. In the laminar-inflow case, we have found that the POD modes related to the tip and root vortices do not contribute positively to the wake recovery, but they rather sustains the velocity gradient, as already established by Lignarolo et al. (2015) for a wind-turbine model. Whereas, in the turbulent-inflow case, all the most energetic modes contribute positively to wake recovery. These results clearly indicate that inflow turbulence should be taken into account for accurately estimate the entrainment process in the wake of wind turbines. NREL 5MW wind turbine, POD, laminar or turbulent inflow, wake recovery, turbulent kinetic energy entrainment.

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Stability and optimal forcing analysis of a wind turbine wake: Comparison with POD

Cited by 14 publications

References 48 publications

Dynamic-mode-decomposition of the wake of the NREL-5MW wind turbine impinged by a laminar inflow

Dynamic-mode-decomposition of the wake of the NREL-5MW wind turbine impinged by a laminar inflow

Composition of resolvents enhanced by random sweeping for large-scale structures in turbulent channel flows

How incoming turbulence affects wake recovery of an NREL-5MW wind turbine

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