Influence of Turbulence Length Scale and Platform Surge Motion on Wake Dynamics in Tandem Floating Wind Turbines

Abstract

Wake interaction is a key factor limiting the performance of floating offshore wind turbine arrays, yet the combined influence of inflow turbulence structure and platform motion on wake dynamics remains poorly understood. This study examines how the integral length scale of inflow turbulence and platform surge motion shapes wake development and power performance in a tandem configuration of two aligned floating offshore wind turbines separated by five rotor diameters. High-fidelity computational fluid dynamics simulations are performed using OpenFOAM, based on Large-Eddy Simulation with an Actuator-Line Model and the Wall-Adapting Local Eddy-Viscosity subgrid-scale closure. Synthetic turbulent inflows are generated using the Divergence-Free Synthetic Eddy Method, with prescribed integral length scales spanning 0.25-1.25 times the rotor radius. Over this range, increasing the integral length scale naturally leads to higher freestream turbulence intensity, which increases from approximately 1.9% to 7.2%. The corresponding dominant inflow frequencies are extracted from time-resolved velocity signals, yielding Strouhal numbers in the range St approx 0.71 to 0.12. Wake evolution is analyzed through disk-averaged velocity deficits, turbulent kinetic energy distributions, spectral characteristics, vortex topology, and time-averaged power coefficients. The results show that the inflow turbulence integral length scale is the primary parameter controlling wake recovery. Larger integral scales introduce energetic, low-frequency eddies that destabilize the tip-vortex system, enhance lateral and vertical entrainment, and accelerate wake mixing. These mechanisms lead to substantial reductions in the inter-turbine velocity deficit and translate directly into increased downstream power output...

Figures (15)

• Figure 1: Velocity triangle and force decomposition on a blade element for fixed (left) and surging (right) turbine conditions. Surge motion introduces an additional axial velocity component $U_s$, which alters the apparent inflow velocity $U_{\text{rel}}$, the inflow angle $\phi$, and consequently the angle of attack $\alpha$.
• Figure 2: Illustration of in-phase ($\Delta\phi_{S0} = 0$) and anti-phase ($\Delta\phi_{S0} = \pi$) surge motions of tandem floating wind turbines. The top panels depict the relative surge alignment of the upstream and downstream turbines. The bottom plots show the corresponding displacement $p_R(t)$ and surge velocity $U_S(t)$ as functions of the normalized surge phase angle $\phi_S$.
• Figure 3: (a) Overall computational domain with the location of the upstream and downstream turbines. (b) Computational mesh shown in an $x$–$y$ plane. Three levels of grid refinement are applied in the region of interest. The background mesh is generated using blockMesh, while local refinement around the rotors is performed using snappyHexMesh.
• Figure 4: Assessment of LES resolution quality: (top) resolved turbulent kinetic energy $K_\text{res}$; (middle) SGS-modeled TKE $K_\text{SGS}$; (bottom) ratio $K_\text{res}/(K_\text{res} + K_\text{SGS})$ demonstrating the dominance of resolved turbulence.
• Figure 5: Iso-surface visualizations of the instantaneous kinematic pressure ($p=\Delta p/\rho = -8$ m$^2$/s$^2$) and Q criterion ($Q=0.25$ s$^{-2}$) fields for both fixed and surge cases. Sub-figures (a) and (b) correspond to the fixed configuration, while (c) and (d) illustrate the surge configuration, the upstream turbine prescribes surge motion while the downstream one remains fixed.