Towards better uncertainty estimates for turbulence statistics

Benedict, L. H.; Gould, Richard D.

doi:10.1007/s003480050030

Cited by 473 publications

(188 citation statements)

References 14 publications

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“…the worst case: highest turbulence intensity 27% and largest integral scales 0.5m). For a 95% confidence interval, 3.3% error is obtained for the mean velocity, 8.7% for the root-mean-square velocity, 30% for the skewness and 121% for the Kurtosis [4]. These statistical errors are reduced to 0.7%, 3.3%, 11.3% and 45.3%, respectively, for the DIT configuration at the worst location.…”

Section: Experimental Set-upmentioning

confidence: 86%

Wind turbine wake properties: Comparison between a non-rotating simplified wind turbine model and a rotating model

Aubrun

Loyer

Hancock

et al. 2013

Journal of Wind Engineering and Industrial Aerodynamics

111

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Section: Experimental Set-upmentioning

confidence: 86%

Wind turbine wake properties: Comparison between a non-rotating simplified wind turbine model and a rotating model

Aubrun

Loyer

Hancock

et al. 2013

Journal of Wind Engineering and Industrial Aerodynamics

111

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“…The measurement error affecting the instantaneous velocity was estimated to be approximately 1% of the free stream value (Raffel et al 24 ). The statistical uncertainties relative to the free stream velocity were estimated to be 0.9% and 0.6% for the mean and the RMS of the fluctuations, respectively (Benedict and Gould 25 ), based on RMS fluctuations of approximately 20% the free stream velocity. The uncertainty on the out-of-plane component of the velocity was approximately three times higher than the in-plane components, considering the stereoscopic viewing angle (Prasad 26 ).…”

Section: B Measurements Apparatus and Proceduresmentioning

confidence: 99%

Low-frequency behavior of the turbulent axisymmetric near-wake

et al. 2016

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The turbulent wake past an axisymmetric body is investigated with time-resolved stereoscopic particle image velocimetry (PIV) at a Reynolds number ReD = 6.7 × 104 based on the object diameter. The azimuthal organization of the near-wake is studied at different locations downstream of the trailing edge. The time-averaged velocity field features a circular shear layer bounding a region of recirculating flow. Inspection of instantaneous PIV snapshots reveals azimuthal meandering of the reverse flow region with a significant radial offset with respect to the time-averaged position. The backflow meandering appears as the major contribution to the near-wake dynamics in proximity of the base, whereas closer to the rear-stagnation point, the shear layer fluctuations become important. For x/D ≤ 0.75, the time-history and probability distributions of the backflow centroid position allow to identify this motion with an irregular precession about the model symmetry axis occurring at time scales in the order of 103 D/U∞ or higher. The first two modes obtained by snapshot proper orthogonal decomposition of the velocity fluctuations can be related to an anti-symmetric mode of azimuthal wave-number m = 1 reflecting a radial displacement of the separated flow region, while the third and fourth proper orthogonal decomposition modes are identified with a second mode pair m = 2 and are representing wake ovalization. Close to the base, a third axisymmetric mode m = 0 is identified, corresponding to a streamwise pulsation of the reverse flow region. Based on the analysis of the spatial eigen-functions and frequency spectra of the time-coefficients, it is concluded that the anti-symmetric mode m = 1 is associated with the backflow instability in the very-low frequency range StD = 10−4/10−3 close to separation, whereas more downstream it reflects the fluctuations related to the shear layer development.

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“…This ensures that the bias error of the PIV velocity measurements is less than 1% of the full-scale velocity (given that the sub-pixel determination has an uncertainty of about ±0.1 pixels -see Adrian & Westerweel 2011). The overall uncertainty in turbulence quantities was determined, following Benedict & Gould (1996) and was found to be less than 1% in the mean velocity, 5% and 8% for the streamwise and normal turbulence intensities and 10% for the shear stresses. These values are also in line with previous PIV-based studies on rough-wall turbulent flows (e.g.…”

Section: Particle Image Velocimetrymentioning

confidence: 99%

Effects of frontal and plan solidities on aerodynamic parameters and the roughness sublayer in turbulent boundary layers

Placidi

Ganapathisubramani

2015

J. Fluid Mech.

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Citation: Placidi, M. & Ganapathisubramani, B. (2015). Effects of frontal and plan solidities on aerodynamic parameters and the roughness sublayer in turbulent boundary layers. Journal of Fluid Mechanics, 782, pp. 541-566. doi: 10.1017Mechanics, 782, pp. 541-566. doi: 10. /jfm.2015 This is the accepted version of the paper.This version of the publication may differ from the final published version. Experiments were conducted in the fully-rough regime on surfaces with large relative roughness height (h/δ ≈ 0.1, where h is the roughness height and δ is the boundary layer thickness). The surfaces were generated by distributed LEGO TM bricks of uniform height, arranged in different configurations. Measurements were made with both floating-element drag-balance and high-resolution particle image velocimetry on six configurations with different frontal solidity, λ F , at fixed plan solidity, λ P , and vice versa, for a total of twelve rough-wall cases. Results indicate that the drag reaches a peak value λ F ≈ 0.21 or a constant λ P = 0.27, whilst it monotonically decreases for increasing values of λ P for a fixed λ F = 0.15. This is in contrast with previous studies in the literature based on cube roughness that show a peak in drag for both λ F and λ P variations. The influence of surface morphology on the depth of the roughness sublayer (RSL) is also investigated. Its depth is found to be inversely proportional to the roughness length, y 0 . A decrease in y 0 is usually accompanied by a thickening of the the RSL and vice-versa. Proper orthogonal decomposition analysis was also employed. The shapes of the most energetic modes calculated using the data across the entire boundary layer are found to be selfsimilar across the twelve rough-walls cases, however, when the analysis is restricted to the roughness sublayer, differences that depend on the wall morphology are apparent. Moreover, the energy content of the POD modes within the RSL suggest that the effect of increased frontal solidity is to redistribute the energy towards the larger-scales (i.e. larger portion of energy is within the first few modes) whilst the opposite is found for variation of plan solidity. Permanent

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Towards better uncertainty estimates for turbulence statistics

Cited by 473 publications

References 14 publications

Wind turbine wake properties: Comparison between a non-rotating simplified wind turbine model and a rotating model

Wind turbine wake properties: Comparison between a non-rotating simplified wind turbine model and a rotating model

Low-frequency behavior of the turbulent axisymmetric near-wake

Effects of frontal and plan solidities on aerodynamic parameters and the roughness sublayer in turbulent boundary layers

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