Spatio-temporal behavior of the far-wake of a wind turbine model subjected to harmonic motions: Phase averaging applied to Stereo-PIV measurements - dataset

Dataset of the figures present in the article entitled: Spatio-temporal behavior of the far-wake of a wind turbine model subjected to harmonic motions: Phase averaging applied to Stereo-PIV measurements. DOI: 10.5194/wes-2024-95 figure2.csv presents the data for the figure 2 (columns: z, Uinf, Iu, Iv, Iw)surge-0.11.pickle, heave-0.09.pickle, pitch-0.14.pickle, pitch-0.28.pickle present the data for the figures 9, 10, 11, 12. Their structure is: Uhub, the velocity at hub heightyz, the y and z coordinatesUabl, the velocity field of the inflowPabl, the available power of the inflowphase, the phase-averaged results, with:Dt, the phasesmotion, the coordinates of the motion (Tx, Tz, Ry)Du, the velocity deficit field in FFoRDu_m, the velocity deficit field in MFoRwkc, the wake centre coordinatesSwk, the wake surfaceP, the available power in FFoRPm, the available power in MFoRvar, the standard deviation of the phase-averaged results, with:wkcSwkPPmAnd fixed.pickle present the time-averaged data of the fixed case for the figures 9, 10, 11, 12, with:Uhub, the velocity at hub heightyz, the y and z coordinatesUabl, the velocity field of the inflowPabl, the available power of the inflowwkc, the wake centre coordinatesSwk, the wake surfaceP, the available power in FFoRPm, the available power in MFoR More details are available in the article, Sect. 2.3.See the website https://docs.python.org/3/library/pickle.html for details about the library pickle, and to load the files.