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70 C. Wagner 〈u〉 20 15 10 5 ——— LES Wagner –––– DNS Kim et al. DNS underresolved LES dyn.Smagorinsky 10−1 100 101 102 0 (y+H/2). Re τ 4 2 0 −2 ——— R xx –––– R yy R zz (−R xz −t xz ) .0 .1 .2 .3 .4 .5 y Fig. 12.3. Mean velocity profiles calculated in LES and DNS (left).Profilesofthe deviatoric part of the Reynolds stress tensor (right) calculated in LES with the scale similarity model and compared to DNS data by Kim et al.) (denoted by symbols) Reynolds numbers he obtained values for CL of the order of 1, but with a significant variation in wall normal direction. Again CL was statistically averaged to enforce the necessary smoothness of CL, which is necessary for conserving the high correlation between τij and Lij In order to give an impression on the performance of the different described subgrid scale models, results of LES of a fully developed turbulent channel flow performed for a Reynolds number Reτ = 360 are presented in Fig. 12.3. For both, the mean velocity profile and the resulting deviatoric part of the Reynolds stress tensor Rij = 〈uiuj〉 −〈ui〉〈uj〉 −1/3(〈ukuk〉 −〈uk〉〈uk〉)δij which are compared to the according data of Kim et al. excellent agreement is obtained while the mean values of the underresolved DNS and of the LES with the Smagorinky model shows considerable discrepiances. 12.7 Conclusion The analysis of the eddy viscosity concept which is applied in most RANS and traditional LES turbulence models showed that such models are not able to reliably predict nonisotropic flows. Therefore, if such simulations are performed to optimize or analyse rotor blades of wind turbines, the obtained results have to be interpreted with caution. References 1. Choi H, Moin P, Kim J (1992) Turbulent drag reduction: studies of feeedback control and flow over riplets, Rep. TF-55, Department of Mechanical Engineering, Stanford University, Stanford, CA
12 Turbulence Modelling and Numerical Flow Simulation 71 2. Frahnert H, Dallmann U Ch (2002) Examination of the eddy-viscosity concept regarding its physical justification. In: Wagner S, Rist U, Heinemann J, Hilbig R. (eds) New Results in Numerical and Experimental Fluid Mechanics III Springer, Berlin Heidelberg New York 3. Germano, M: Turbulence: the filtering approach; J. Fluid Mech. A 5:1282-84 (1992) 4. Kim J, Moin P, Moser R (1987) J. Fluid Mech. A 177:133–166 5. Lilly DK (1992) Phys. Fluids A 4:633–635 6. Liu S, Meneveau D, Katz J (1994) J. Fluid Mech. 275:83–119 7. Smagorinsky J (1963) Mon. Weather Rev. 91–99 8. Wagner C (2001) Z. Angew. Math. Mech. 81, Suppl. 3:491–492 9. Wilcox D C (1988) AIAA Journal, 26:1299–1310
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Wind Energy Proceedings of the Euro
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Prof. Dr. Joachim Peinke Dr. Stepha
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VI Preface been presented, spanning
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VIII Contents 3.3 Stochastic Wind F
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X Contents 12.6 Subgrid Scale Turbu
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XII Contents 22 Stochastic Small-Sc
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XIV Contents 32 Handling Systems Dr
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XVI Contents 41 3D Numerical Simula
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XVIII Contents 51 Comparing WAsP an
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XX Contents 58.3 Ultra-High Perform
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XXII List of Contributors Lars Berg
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XXIV List of Contributors Renata Gn
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XXVI List of Contributors A. Kiss D
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XXVIII List of Contributors El˙zbi
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XXX List of Contributors Ivo Sláde
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1 Offshore Wind Power Meteorology B
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1 Offshore Wind Power Meteorology 3
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1 Offshore Wind Power Meteorology 5
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2 Wave Loads on Wind-Power Plants i
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Trubaduren 2 Wave Loads on Wind-Pow
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Base moment (10 6 Nm) 0.4 0.2 −0.
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2 Wave Loads on Wind-Power Plants i
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3 Time Domain Comparison of Simulat
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3 Time Domain Comparison Using Cons
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Page 51 and 52: 4 Mean Wind and Turbulence in the A
Page 57 and 58: 5 Wind Speed Profiles above the Nor
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Page 61 and 62: Height [m] 100 90 80 70 60 50 40 30
Page 63 and 64: 6 Fundamental Aspects of Fluid Flow
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Page 85 and 86: 10 On the Atmospheric Flow Modellin
Page 91 and 92: 11 Comparison of Logarithmic Wind P
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Page 95 and 96: 12 Turbulence Modelling and Numeric
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Page 131 and 132: Log10 E(k)*k**(5/3) 6 4 2 0 5/3 cor
Page 133 and 134: 17.3 Discussion and Conclusion 17 W
Page 135 and 136: 18 Boundary-Layer Influence on Extr
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Page 139 and 140: 18.6 Concluding Remarks 18 Boundary
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Page 145 and 146: 20 Superposition Model for Atmosphe
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21 Extreme Events Under Low-Frequen
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22 Stochastic Small-Scale Modelling
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p(σ⏐u) 1 0.8 0.6 0.4 0.2 22 Stoc
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22 Stochastic Small-Scale Modelling
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23 Quantitative Estimation of Drift
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24 Scaling Turbulent Atmospheric St
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24 Scaling Turbulent Atmospheric St
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25 Wind Farm Power Fluctuations P.
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25 Wind Farm Power Fluctuations 141
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d rc q rc V 0 q V 25 Wind Farm Powe
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References 25 Wind Farm Power Fluct
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26 Network Perspective of Wind-Powe
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27 Phenomenological Response Theory
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28 Turbulence Correction for Power
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28 Turbulence Correction for Power
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29 Online Modeling of Wind Farm Pow
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29 Online Modeling of Wind Farm Pow
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30 Uncertainty of Wind Energy Estim
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31 Characterisation of the Power Cu
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32 Handling Systems Driven by Diffe
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32 Handling Systems Driven by Diffe
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33 Experimental Researches of Chara
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33 Experimental Researches of Chara
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34 Methodical Failure Detection in
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34 Methodical Failure Detection in
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35 Modelling of the Transition Loca
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35 Modelling an Airfoil with Surfac
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(Cl/Cd)max 120 110 100 90 80 70 60
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35 Modelling an Airfoil with Surfac
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36 Helicopter Aerodynamics with Emp
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37 Determination of Angle of Attack
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37 Determination of Angle of Attack
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Drag coefficient 0.5 0.4 0.3 0.2 0.
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38 Unsteady Characteristics of Flow
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PSD PSD 38 Unsteady Characteristics
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39 Aerodynamic Multi-Criteria Shape
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39 Multi-Criteria Shape Optimizatio
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39 Multi-Criteria Shape Optimizatio
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40 Rotation and Turbulence Effects
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Cp Xsep/c 1 0.6 0.2 −0.2 −0.6
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Standard deviation of Cp 0.7 0.6 0.
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41 3D Numerical Simulation and Eval
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41 3D-CFD-Simulation of a Wind Turb
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42 Performance of the Risø-B1 Airf
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42 Performance of the Risø-B1 Airf
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43 Aerodynamic Behaviour of a New T
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44 Numerical Simulation of Dynamic
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44 Numerical Simulation of Dynamic
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45 Modeling of the Far Wake behind
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8 6 uz 4 2 45 Modeling of the Far W
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46 Stability of the Tip Vortices in
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46 Stability of the Tip Vortices in
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47 Modelling Turbulence Intensities
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48 Numerical Computations of Wind T
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Z X Y 48 Numerical Computations of
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References 48 Numerical Computation
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49 Modelling Wind Turbine Wakes wit
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U mean / U ref 1 0.9 0.8 0.7 49 Mod
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49.5 Conclusion 49 Modelling Wind T
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50 Prediction of Wind Turbine Noise
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0.8 0.6 0.4 0.2 −0.2 −0.4 −0.
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51 Comparing WAsP and Fluent for Hi
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Table 51.1. Measurements and simula
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51 Comparing WAsP and Fluent for Hi
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52 Fatigue Assessment of Truss Join
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53 Advances in Offshore Wind Techno
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Simulation Measurement pitch angle
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53 Advances in Offshore Wind Techno
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54 Benefits of Fatigue Assessment w
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∆σN [N/mm²] 100 10 54 Benefits
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55 Extension of Life Time of Welded
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Transverse residual stresses [N/mm
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56 Damage Detection on Structures o
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56 Damage Detection on Structures o
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57 Influence of the Type and Size o
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[W/m 2 ] q t [W/m 5000 4000 3000 20
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58 High-cycle Fatigue of “Ultra-H
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(a) (b) 450 Load [kN] 400 350 300 2
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59 A Modular Concept for Integrated
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60 Solutions of Details Regarding F
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SR 1000 800 600 400 200 100 80 60 4
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60 Solutions of Details Regarding F
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61 On the Influence of Low-Level Je
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Relative Power and Loading [%] 61 O
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62 Reliability of Wind Turbines Exp
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62 Reliability of Wind Turbines 331
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