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88 J. Mann<br />

vector between two points is − 4<br />

5 times the dissipation of kinetic energy ε times<br />

the separation distance r. It is approximately true for high Reynolds number<br />

flows when r is in the inertial subrange, and, assuming an infinitely long<br />

inertial subrange, can be derived rigourously. Despite this fact it simplifies the<br />

simulation algorithms immensely to assume the velocity field to be a gaussian<br />

random field. Furthermore, it is not clear how important the departure from<br />

gaussianity is for the dynamic loads, though some attempts to quantify this<br />

has been undertaken. For example, for a turbine in rather complex terrain<br />

some loads increased by 15% comparing a non-gaussian simulation with a<br />

gaussian with the same second order structure [7].<br />

In this paper we from hereon assume gaussianity. We furthermore assume<br />

Taylor’s hypothesis to be valid<br />

ũ(x, y, z, t) =ũ(x − Ut,y,z,0), (15.1)<br />

where x is the coordinate in the mean flow direction, U the mean wind speed.<br />

The velocity vector is denoted by ũ and the fluctuations around the mean is<br />

u. All second order statistics of the fluctuations can be expressed in terms of<br />

the covariance tensor<br />

Rij(r) =〈ui(x)uj(x + r)〉 . (15.2)<br />

It does not depend on x if homogeneity is assumed. This is usually a good<br />

assumption for the horizontal directions x and y, but less optimal for the<br />

vertical.<br />

The Fourier transform of the covariance tensor<br />

Φij(k) = 1<br />

(2π) 3<br />

�<br />

Rij(r)exp(−ik · r)dr, (15.3)<br />

is called the spectral velocity tensor. This has been modelled by Mann [4] for a<br />

homogeneous shear layer, and compared well to atmospheric surface-layer data<br />

over flat terrain. Based on this model a Fourier simulation algorithm, which<br />

essentially is a superposition of sine-waves in 3D space, may be devised [5].<br />

The model by Veers [10], which was improved by Winkelaar [11], is based<br />

on one-point spectra and coherences, i.e. the absolute value of the normalized<br />

cross-spectra. The phase of the cross-spectra is typically ignored and<br />

so is incompressibility. Also, empirical information of all cross-spectra is not<br />

available.<br />

A group at Risø has simulated 3D fields by the model and sampled the<br />

velocities on a helix emulating the passage of a point on a wind turbine blade<br />

through the air [8]. They compared this with measurements made by a pitot<br />

tube mounted on a rotating blade. The comparison is shown in the right plot<br />

of Fig. 15.1. The left plot in this figure shows the helix sampled spectra from<br />

a Veers simulation of only the longitudinal wind component (lower points)<br />

and of the two horizontal component. It seems to be important to simulate<br />

all three components of the velocity field to obtain realistic spectra.

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